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Llama","name":"meta-llama","type":"org","isHf":false,"isHfAdmin":false,"isMod":false,"plan":"enterprise","followerCount":85778,"isUserFollowing":false},"canReadRepoSettings":false,"canWriteRepoContent":false,"canDisable":false,"model":{"author":"meta-llama","cardData":{"language":["en","de","fr","it","pt","hi","es","th"],"license":"llama3.1","base_model":"meta-llama/Meta-Llama-3.1-8B","pipeline_tag":"text-generation","tags":["facebook","meta","pytorch","llama","llama-3"],"extra_gated_prompt":"### LLAMA 3.1 COMMUNITY LICENSE AGREEMENT\nLlama 3.1 Version Release Date: July 23, 2024\n\"Agreement\" means the terms and conditions for use, reproduction, distribution and modification of the Llama Materials set forth herein.\n\"Documentation\" means the specifications, manuals and documentation accompanying Llama 3.1 distributed by Meta at https://llama.meta.com/doc/overview.\n\"Licensee\" or \"you\" means you, or your employer or any other person or entity (if you are entering into this Agreement on such person or entity’s behalf), of the age required under applicable laws, rules or regulations to provide legal consent and that has legal authority to bind your employer or such other person or entity if you are entering in this Agreement on their behalf.\n\"Llama 3.1\" means the foundational large language models and software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Meta at https://llama.meta.com/llama-downloads.\n\"Llama Materials\" means, collectively, Meta’s proprietary Llama 3.1 and Documentation (and any portion thereof) made available under this Agreement.\n\"Meta\" or \"we\" means Meta Platforms Ireland Limited (if you are located in or, if you are an entity, your principal place of business is in the EEA or Switzerland) and Meta Platforms, Inc. 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If you access or use Llama 3.1, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of this policy can be found at [https://llama.meta.com/llama3_1/use-policy](https://llama.meta.com/llama3_1/use-policy)\n#### Prohibited Uses\nWe want everyone to use Llama 3.1 safely and responsibly. You agree you will not use, or allow others to use, Llama 3.1 to:\n 1. Violate the law or others’ rights, including to:\n 1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:\n 1. Violence or terrorism\n 2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material\n 3. Human trafficking, exploitation, and sexual violence\n 4. 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1.7 5.2l.4-.8h3.8v4.8l-1 .5Z"></path><path fill="#000" fill-rule="evenodd" d="M9.9 3.2c.8.5 1 1.5.5 2.3L7 10c-.6.9-2 .9-2.6 0L1.3 5.5c-.5-.8-.3-1.8.5-2.3l3.2-2c.5-.3 1.2-.3 1.7 0l3.2 2ZM6.4 5h3l-3 4.2V5ZM5.3 5h-3l3 4.2V5Zm3.8-1L6 2a.5.5 0 0 0-.5 0L2.6 4H9Z" clip-rule="evenodd"></path></svg><!--]--><!--]--> <!--[-1--><!--]--> <!--[-1--><span>text-generation-inference</span><!--]--> <!--[-1--><!--]--> <!--[--><!--]--></div><!----></a><!----><!--]--><!--]--><!--]--><!--]--><!--]--><!--[-1--><!--[--><!--[0--><div class="relative inline-block "><button class="group mr-1 mb-1 md:mr-1.5 md:mb-1.5 rounded-full rounded-br-none " type="button"><!--[0--><div><div class="tag rounded-full tag-white relative rounded-br-none pr-2.5"><!--[8--><!--[--><svg class="-mr-1 text-gray-400" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 12 12" preserveAspectRatio="xMidYMid meet" fill="none"><path fill="currentColor" fill-rule="evenodd" d="M8.007 1.814a1.176 1.176 0 0 0-.732-.266H3.088c-.64 0-1.153.512-1.153 1.152v6.803c0 .64.513 1.152 1.153 1.152h5.54c.632 0 1.144-.511 1.144-1.152V3.816c0-.338-.137-.658-.412-.887L8.007 1.814Zm-1.875 1.81c0 .695.55 1.253 1.244 1.253h.983a.567.567 0 0 1 .553.585v4.041c0 .165-.119.302-.283.302h-5.55c-.156 0-.275-.137-.275-.302V2.7a.284.284 0 0 1 .284-.301h2.468a.574.574 0 0 1 .434.19.567.567 0 0 1 .142.395v.64Z" clip-rule="evenodd" fill-opacity=".8"></path><path fill="currentColor" fill-opacity=".2" fill-rule="evenodd" d="M6.132 3.624c0 .695.55 1.253 1.244 1.253h.97a.567.567 0 0 1 .566.585v4.041c0 .165-.119.302-.283.302h-5.55c-.156 0-.275-.137-.275-.302V2.7a.284.284 0 0 1 .284-.301h2.468a.567.567 0 0 1 .576.585v.64Z" clip-rule="evenodd"></path></svg><!--]--><!--]--> <!--[-1--><!--]--> <!--[1--><!--[0--><span class="-mr-2 text-gray-400">arxiv:</span><!--]--> <span>2204.05149</span><!--]--> <!--[-1--><!--]--> <!--[--><!--[0--><div 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meta-llama/Llama-3.1-8B-Instruct with Transformers:</p> <!--[--><!--[-1--><!--]--> <pre># Use a pipeline as a high-level helper107from transformers import pipeline108109pipe = pipeline("text-generation", model="meta-llama/Llama-3.1-8B-Instruct")110messages = [111 {"role": "user", "content": "Who are you?"},112]113pipe(messages)</pre><!--[-1--><!--]--> <pre># Load model directly114from transformers import AutoTokenizer, AutoModelForCausalLM115116tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B-Instruct")117model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct", device_map="auto")118messages = [119 {"role": "user", "content": "Who are you?"},120]121inputs = tokenizer.apply_chat_template(122 messages,123 add_generation_prompt=True,124 tokenize=True,125 return_dict=True,126 return_tensors="pt",127).to(model.device)128129outputs = model.generate(**inputs, max_new_tokens=40)130print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))</pre><!--]--><!--]--><!----></li><!--]--> <!--[0--><li class="w-56 px-3 py-1.5 text-sm text-gray-500">Inference</li> <li><!----><button class="flex w-full cursor-pointer items-center whitespace-nowrap px-3 py-1.5 text-left leading-tight hover:bg-gray-50 dark:hover:bg-gray-800 pl-3 " type="button"><!--[0--><svg class="mr-1.5 flex-none" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 12 12"><path fill-rule="evenodd" clip-rule="evenodd" d="M7.587 8.498a.613.613 0 0 0 .812-.915l-.004-.004a.61.61 0 0 0-.27-.157l-.538 1.076Zm.935-1.871a.612.612 0 0 0 .211.037h.006a.613.613 0 0 0 .33-1.13l-.547 1.093Zm.057-2.531a.613.613 0 0 0-1.046-.444l-.005.005a.61.61 0 0 0-.178.402h.969a.93.93 0 0 1 .26.037ZM3.57 5.518l-.549 1.097a.613.613 0 0 1 .24-1.177h.007a.61.61 0 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2.214c-5.776-10.717-11.576-21.707-17.187-32.793-6.359-12.562-12.54-25.213-18.813-37.818-7.388-14.847-14.768-29.696-22.19-44.525-8.9-17.78-17.885-35.518-26.756-53.313-14.122-28.33-28.171-56.694-42.28-85.03-1.384-2.78-2.964-5.462-4.752-8.736 2.163-.132 3.585-.295 5.007-.295 40.662-.014 81.325.008 121.987-.05 3.117-.005 5.813-.059 5.094 5.157.006 84.33-.002 167.77.002 251.208 0 1.327.143 2.654.219 3.981"></path><path fill="#D7D8D9" d="M197.123 394.504c31.315-.378 62.802-.44 94.288-.5 1.97-.005 3.94-.001 6.2-.001 4.543-17.152 8.963-33.967 13.452-50.764 8.479-31.729 17.08-63.425 25.467-95.178 4.694-17.772 8.899-35.674 13.62-53.44 4.978-18.74 10.442-37.351 15.446-56.085 4.668-17.475 8.99-35.042 13.507-52.556 1.574-6.102 3.28-12.17 5.01-18.646 2.473-1.275 4.861-2.156 8.033-3.328-2.087 8.294-3.922 15.954-5.95 23.563-3.664 13.747-7.485 27.451-11.163 41.194-6.513 24.331-13.055 48.655-19.422 73.024-6.365 24.36-12.432 48.796-18.823 73.147-3.322 12.66-7.213 25.171-10.574 37.822-4.892 18.406-9.477 36.893-14.313 55.314-2.477 9.434-5.3 18.778-7.79 28.209-.796 3.017-2.461 3.779-5.397 3.77-31.831-.083-63.664-.152-95.494.07-4.283.03-4.791-2.612-6.097-5.615"></path><path fill="#D8D8D8" d="M194.348 389.978c-.35-1.057-.492-2.384-.492-3.71-.004-83.44.004-166.88.071-250.782 1.527-.384 2.994-.306 5.123-.192v6.588c0 73.977-.002 147.954.012 221.932 0 1.82.177 3.64.532 5.765-1.483 6.912-3.228 13.52-5.246 20.399"></path></svg><!--]--><!--]--><!----> <span class="truncate">vLLM</span> <!--[-1--><!--]--><!----><!--]--><!----></a><!----> <!--[0--><p>How to use meta-llama/Llama-3.1-8B-Instruct with vLLM:</p> <!--[--><!--[0--><h5>Install from pip and serve model</h5><!--]--> <pre># Install vLLM from pip:131pip install vllm132# Start the vLLM server:133vllm serve "meta-llama/Llama-3.1-8B-Instruct"134# Call the server using curl (OpenAI-compatible API):135curl -X POST "http://localhost:8000/v1/chat/completions" \136 -H "Content-Type: application/json" \137 --data '{138 "model": "meta-llama/Llama-3.1-8B-Instruct",139 "messages": [140 {141 "role": "user",142 "content": "What is the capital of France?"143 }144 ]145 }'</pre><!--[0--><h5>Use Docker</h5><!--]--> <pre>docker model run hf.co/meta-llama/Llama-3.1-8B-Instruct</pre><!--]--><!--]--><!----></li><!--]--><!--[-1--><li><!----><a class="flex w-full cursor-pointer items-center whitespace-nowrap px-3 py-1.5 text-left leading-tight hover:bg-gray-50 dark:hover:bg-gray-800 pl-3 " href="/meta-llama/Llama-3.1-8B-Instruct?local-app=sglang"><!--[0--><!--[0--><!--[--><svg class="text-black mr-1.5 flex-none " width="1em" height="1em" viewBox="0 0 12 12" fill="none" xmlns="http://www.w3.org/2000/svg" focusable="false" role="img" aria-hidden="true" preserveAspectRatio="xMidYMid meet"><path d="M8.648 3.182c0 1.402-1.656 2.805-3.312 2.805" stroke="#A5300F" stroke-width=".5" stroke-miterlimit="8"></path><path d="M4.031 5.12c1.08 0 2.158 1.61 2.158 3.221" stroke="#A5300F" stroke-width=".5" stroke-miterlimit="8"></path><path d="M3.048 6.238a1.322 1.322 0 1 0 0-2.644 1.322 1.322 0 0 0 0 2.644ZM8.955 4.163a1.322 1.322 0 1 0 0-2.643 1.322 1.322 0 0 0 0 2.643ZM7.317 8.34H5.053a.35.35 0 0 0-.35.35v1.399c0 .193.157.35.35.35h2.264a.35.35 0 0 0 .35-.35v-1.4a.35.35 0 0 0-.35-.35Z" fill="#FADDCD" stroke="#A5300F" stroke-width=".5"></path><path d="M6.392 8.88c.047.02.069.073.05.12l-.375.906a.092.092 0 1 1-.17-.07l.374-.906a.092.092 0 0 1 .12-.05Zm-.776.055a.093.093 0 0 1 .131 0 .093.093 0 0 1 0 .13l-.345.343.358.359a.093.093 0 0 1 0 .13.092.092 0 0 1-.13 0l-.424-.423a.092.092 0 0 1-.026-.066c0-.024.009-.048.026-.065l.41-.408Zm1 0a.093.093 0 0 1 .131 0l.41.408a.093.093 0 0 1 .027.065c0 .025-.01.048-.027.066l-.424.423a.092.092 0 0 1-.13 0 .093.093 0 0 1 0-.13l.358-.359-.344-.343a.093.093 0 0 1 0-.13Z" fill="#A5300F"></path></svg><!--]--><!--]--><!----> <span class="truncate">SGLang</span> <!--[-1--><!--]--><!----><!--]--><!----></a><!----> <!--[0--><p>How to use meta-llama/Llama-3.1-8B-Instruct with SGLang:</p> <!--[--><!--[0--><h5>Install from pip and serve model</h5><!--]--> <pre># Install SGLang from pip:146pip install sglang147# Start the SGLang server:148python3 -m sglang.launch_server \149 --model-path "meta-llama/Llama-3.1-8B-Instruct" \150 --host 0.0.0.0 \151 --port 30000152# Call the server using curl (OpenAI-compatible API):153curl -X POST "http://localhost:30000/v1/chat/completions" \154 -H "Content-Type: application/json" \155 --data '{156 "model": "meta-llama/Llama-3.1-8B-Instruct",157 "messages": [158 {159 "role": "user",160 "content": "What is the capital of France?"161 }162 ]163 }'</pre><!--[0--><h5>Use Docker images</h5><!--]--> <pre>docker run --gpus all \164 --shm-size 32g \165 -p 30000:30000 \166 -v ~/.cache/huggingface:/root/.cache/huggingface \167 --env "HF_TOKEN=<secret>" \168 --ipc=host \169 lmsysorg/sglang:latest \170 python3 -m sglang.launch_server \171 --model-path "meta-llama/Llama-3.1-8B-Instruct" \172 --host 0.0.0.0 \173 --port 30000174# Call the server using curl (OpenAI-compatible API):175curl -X POST "http://localhost:30000/v1/chat/completions" \176 -H "Content-Type: application/json" \177 --data '{178 "model": "meta-llama/Llama-3.1-8B-Instruct",179 "messages": [180 {181 "role": "user",182 "content": "What is the capital of France?"183 }184 ]185 }'</pre><!--]--><!--]--><!----></li><!--]--><!--]--> <!--[0--><!--[0--><!--[--><!--[-1--><li><!----><a class="flex w-full cursor-pointer items-center whitespace-nowrap px-3 py-1.5 text-left leading-tight hover:bg-gray-50 dark:hover:bg-gray-800 pl-3 " href="/meta-llama/Llama-3.1-8B-Instruct?local-app=docker-model-runner"><!--[0--><!--[0--><!--[--><svg class="text-black mr-1.5 flex-none text-[#1D63ED]!" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 16 12"><path d="M2.91013 5.125H1.50107C1.43433 5.125 1.38242 5.07308 1.375 4.99892L1.375 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4.99892L9.2138 3.73806C9.2138 3.66389 9.27313 3.61198 9.33987 3.61198H10.7489C10.8231 3.61198 10.875 3.67131 10.875 3.73806L10.875 4.99892C10.875 5.07308 10.8157 5.125 10.7489 5.125ZM14.5381 3.98439C15.3989 3.98439 15.7996 4.29008 15.8442 4.32736L16 4.4392L15.9332 4.63306C15.8219 4.90147 15.6661 5.14006 15.4583 5.33392C15.1466 5.64707 14.5826 6.01241 13.6699 6.01241L13.5215 6.01241C13.1579 6.95186 12.6607 8.01061 11.8221 8.95752C11.325 9.52417 10.7387 10.0088 10.0857 10.3891C9.29169 10.8439 8.43089 11.157 7.53298 11.3211C6.88738 11.4404 6.23436 11.5 5.58134 11.5C4.1343 11.5 2.85052 11.2241 2.06392 10.7395C1.36638 10.307 0.824667 9.59873 0.461052 8.64437C0.141962 7.77202 -0.0138728 6.84748 0.000968518 5.92294C0.000968494 5.64707 0.22359 5.42339 0.498155 5.42339L11.0356 5.42339C11.1691 5.41593 11.8073 5.36374 12.2006 5.14006C11.8741 4.61814 11.7776 4.00676 11.9335 3.35809C12.0151 3.02257 12.1561 2.69451 12.3416 2.40372L12.49 2.1875L12.7201 2.32171C12.7225 2.32369 12.729 2.32796 12.7389 2.33455C12.8788 2.42733 13.7104 2.97895 13.8628 4.04404C14.0855 4.00676 14.3155 3.98439 14.5381 3.98439Z" fill="currentColor"></path></svg><!--]--><!--]--><!----> <span class="truncate">Docker Model Runner</span> <!--[-1--><!--]--><!----><!--]--><!----></a><!----> <!--[0--><p>How to use meta-llama/Llama-3.1-8B-Instruct with Docker Model Runner:</p> <!--[--><!--[-1--><!--]--> <pre>docker model run hf.co/meta-llama/Llama-3.1-8B-Instruct</pre><!--]--><!--]--><!----></li><!--]--><!--]--><!--]--> <!--[-1--><!--]--><!--]--> <!--[0--><li class="w-56"><div class="mx-3 border-t border-gray-200 py-2 text-xs text-gray-600 dark:border-gray-700"><a class="underline decoration-gray-400 hover:decoration-gray-600 dark:hover:decoration-gray-300" href="/models?other=base_model:quantized:meta-llama/Llama-3.1-8B-Instruct"><svg class="size-3 inline-block -ml-0.5 mr-0.5 -translate-y-px" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 12 12"><path d="M1.5 8.25h9V2.253h.75v5.999h-.75V9h-3v1.5H9v.75H3v-.75h1.5V9H1.54v-.748H.75v-6h.75V8.25Zm3.75 2.25h1.5V9h-1.5v1.5Zm2.11-5.749h.786v.786H7.36v.782h-.785v.766H5.79v-.786h.785v-.766h.785v-.777h-.785V3.97h.786v.781ZM5.786 6.318H5v-.786h.786v.786Zm.783-2.351h-.783v.775h-.013v.005h-.768v.782h-.786v-.786H5v-.782h.783v-.78h.786v.786ZM10.5 2.25H1.512V1.5H10.5v.75Z" fill="currentColor"></path></svg><!---->Browse186 Quantizations</a> to use this model in <span class="whitespace-nowrap"><svg class="size-3 inline-block align-text-top translate-y-px" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 12 12"><path fill="currentColor" d="M9.11 9.94c-.26.4-.7.64-1.18.64H3.25l1.83-3.17h5.5zM5.08 7.4H1.42l3.05-5.28c.25-.43.71-.7 1.21-.7h2.86z"></path></svg><!----> llama.cpp</span>, <span class="whitespace-nowrap"><svg class="size-3 inline-block align-text-top translate-y-px" width="1em" height="1em" viewBox="0 0 646 854" fill="none" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" focusable="false" role="img" aria-hidden="true" preserveAspectRatio="xMidYMid meet"><path d="M140.629 0.239929C132.66 1.52725 123.097 5.69568 116.354 10.845C95.941 26.3541 80.1253 59.2728 73.4435 100.283C70.9302 115.792 69.2138 137.309 69.2138 153.738C69.2138 173.109 71.4819 197.874 74.7309 214.977C75.4665 218.778 75.8343 222.15 75.5278 222.395C75.2826 222.64 72.2788 225.092 68.9072 227.789C57.3827 236.984 44.2029 251.145 35.1304 264.08C17.7209 288.784 6.44151 316.86 1.72133 347.265C-0.117698 359.28 -0.608106 383.555 0.863118 395.57C4.11207 423.278 12.449 446.695 26.7321 468.151L31.391 475.078L30.0424 477.346C20.4794 493.407 12.3264 516.64 8.52575 538.953C5.522 556.608 5.15419 561.328 5.15419 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class="whitespace-nowrap"><svg class="size-3 inline-block align-text-top translate-y-px" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path fill="url(#icon-lm-studio-a)" d="M19.337 0H4.663A4.663 4.663 0 0 0 0 4.663v14.674A4.663 4.663 0 0 0 4.663 24h14.674A4.663 4.663 0 0 0 24 19.337V4.663A4.663 4.663 0 0 0 19.337 0"></path><g fill="#fff" opacity=".266"><path d="M15.803 4.35H7.418a1 1 0 0 0 0 2h8.385a1 1 0 0 0 0-2M19.928 7.063h-8.385a1 1 0 0 0 0 2h8.385a1 1 0 0 0 0-2M17.51 9.776H9.125a1 1 0 0 0 0 2h8.385a1 1 0 0 0 0-2M14.523 12.632H6.138a1 1 0 0 0 0 2h8.385a1 1 0 0 0 0-2M17.51 15.345H9.125a1 1 0 1 0 0 2h8.385a1 1 0 1 0 0-2M20.497 18.059h-4.829a1 1 0 1 0 0 1.999h4.829a1 1 0 1 0 0-2"></path></g><g fill="#fff" opacity=".845"><path d="M12.65 4.345H4.265a1 1 0 0 0 0 2h8.385a1 1 0 0 0 0-2M16.775 7.058H8.39a1 1 0 0 0 0 2h8.385a1 1 0 0 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data-props="{"accessButtonString":"Submit","additionalFields":{"First Name":"text","Last Name":"text","Date of birth":"date_picker","Country":"country","Affiliation":"text","Job title":{"type":"select","options":["Student","Research Graduate","AI researcher","AI developer/engineer","Reporter","Other"]},"geo":"ip_location","By clicking Submit below I accept the terms of the license and acknowledge that the information I provide will be collected stored processed and shared in accordance with the Meta Privacy Policy":"checkbox"},"additionalMessage":{"contents":"### LLAMA 3.1 COMMUNITY LICENSE AGREEMENT\nLlama 3.1 Version Release Date: July 23, 2024\n\"Agreement\" means the terms and conditions for use, reproduction, distribution and modification of the Llama Materials set forth herein.\n\"Documentation\" means the specifications, manuals and documentation accompanying Llama 3.1 distributed by Meta at https://llama.meta.com/doc/overview.\n\"Licensee\" or \"you\" means you, or your employer or any other person or entity (if you are entering into this Agreement on such person or entity’s behalf), of the age required under applicable laws, rules or regulations to provide legal consent and that has legal authority to bind your employer or such other person or entity if you are entering in this Agreement on their behalf.\n\"Llama 3.1\" means the foundational large language models and software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Meta at https://llama.meta.com/llama-downloads.\n\"Llama Materials\" means, collectively, Meta’s proprietary Llama 3.1 and Documentation (and any portion thereof) made available under this Agreement.\n\"Meta\" or \"we\" means Meta Platforms Ireland Limited (if you are located in or, if you are an entity, your principal place of business is in the EEA or Switzerland) and Meta Platforms, Inc. (if you are located outside of the EEA or Switzerland).\n \n1. License Rights and Redistribution.\na. Grant of Rights. You are granted a non-exclusive, worldwide, non-transferable and royalty-free limited license under Meta’s intellectual property or other rights owned by Meta embodied in the Llama Materials to use, reproduce, distribute, copy, create derivative works of, and make modifications to the Llama Materials.\nb. Redistribution and Use.\ni. If you distribute or make available the Llama Materials (or any derivative works thereof), or a product or service (including another AI model) that contains any of them, you shall (A) provide a copy of this Agreement with any such Llama Materials; and (B) prominently display “Built with Llama” on a related website, user interface, blogpost, about page, or product documentation. If you use the Llama Materials or any outputs or results of the Llama Materials to create, train, fine tune, or otherwise improve an AI model, which is distributed or made available, you shall also include “Llama” at the beginning of any such AI model name.\nii. If you receive Llama Materials, or any derivative works thereof, from a Licensee as part of an integrated end user product, then Section 2 of this Agreement will not apply to you.\niii. You must retain in all copies of the Llama Materials that you distribute the following attribution notice within a “Notice” text file distributed as a part of such copies: “Llama 3.1 is licensed under the Llama 3.1 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.”\niv. Your use of the Llama Materials must comply with applicable laws and regulations (including trade compliance laws and regulations) and adhere to the Acceptable Use Policy for the Llama Materials (available at https://llama.meta.com/llama3_1/use-policy), which is hereby incorporated by reference into this Agreement.\n2. Additional Commercial Terms. If, on the Llama 3.1 version release date, the monthly active users of the products or services made available by or for Licensee, or Licensee’s affiliates, is greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta, which Meta may grant to you in its sole discretion, and you are not authorized to exercise any of the rights under this Agreement unless or until Meta otherwise expressly grants you such rights.\n3. Disclaimer of Warranty. UNLESS REQUIRED BY APPLICABLE LAW, THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS THEREFROM ARE PROVIDED ON AN “AS IS” BASIS, WITHOUT WARRANTIES OF ANY KIND, AND META DISCLAIMS ALL WARRANTIES OF ANY KIND, BOTH EXPRESS AND IMPLIED, INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING OR REDISTRIBUTING THE LLAMA MATERIALS AND ASSUME ANY RISKS ASSOCIATED WITH YOUR USE OF THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS.\n4. Limitation of Liability. IN NO EVENT WILL META OR ITS AFFILIATES BE LIABLE UNDER ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, TORT, NEGLIGENCE, PRODUCTS LIABILITY, OR OTHERWISE, ARISING OUT OF THIS AGREEMENT, FOR ANY LOST PROFITS OR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL, EXEMPLARY OR PUNITIVE DAMAGES, EVEN IF META OR ITS AFFILIATES HAVE BEEN ADVISED OF THE POSSIBILITY OF ANY OF THE FOREGOING.\n5. Intellectual Property.\na. No trademark licenses are granted under this Agreement, and in connection with the Llama Materials, neither Meta nor Licensee may use any name or mark owned by or associated with the other or any of its affiliates, except as required for reasonable and customary use in describing and redistributing the Llama Materials or as set forth in this Section 5(a). Meta hereby grants you a license to use “Llama” (the “Mark”) solely as required to comply with the last sentence of Section 1.b.i. You will comply with Meta’s brand guidelines (currently accessible at https://about.meta.com/brand/resources/meta/company-brand/ ). All goodwill arising out of your use of the Mark will inure to the benefit of Meta.\nb. Subject to Meta’s ownership of Llama Materials and derivatives made by or for Meta, with respect to any derivative works and modifications of the Llama Materials that are made by you, as between you and Meta, you are and will be the owner of such derivative works and modifications.\nc. If you institute litigation or other proceedings against Meta or any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Llama Materials or Llama 3.1 outputs or results, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by you, then any licenses granted to you under this Agreement shall terminate as of the date such litigation or claim is filed or instituted. You will indemnify and hold harmless Meta from and against any claim by any third party arising out of or related to your use or distribution of the Llama Materials.\n6. Term and Termination. The term of this Agreement will commence upon your acceptance of this Agreement or access to the Llama Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein. Meta may terminate this Agreement if you are in breach of any term or condition of this Agreement. Upon termination of this Agreement, you shall delete and cease use of the Llama Materials. Sections 3, 4 and 7 shall survive the termination of this Agreement.\n7. Governing Law and Jurisdiction. This Agreement will be governed and construed under the laws of the State of California without regard to choice of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement. The courts of California shall have exclusive jurisdiction of any dispute arising out of this Agreement.\n### Llama 3.1 Acceptable Use Policy\nMeta is committed to promoting safe and fair use of its tools and features, including Llama 3.1. If you access or use Llama 3.1, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of this policy can be found at [https://llama.meta.com/llama3_1/use-policy](https://llama.meta.com/llama3_1/use-policy)\n#### Prohibited Uses\nWe want everyone to use Llama 3.1 safely and responsibly. You agree you will not use, or allow others to use, Llama 3.1 to:\n 1. Violate the law or others’ rights, including to:\n 1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:\n 1. Violence or terrorism\n 2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material\n 3. Human trafficking, exploitation, and sexual violence\n 4. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.\n 5. Sexual solicitation\n 6. Any other criminal activity\n 3. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals\n 4. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services\n 5. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices\n 6. Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws\n 7. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama Materials\n 8. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system\n2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama 3.1 related to the following:\n 1. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State\n 2. Guns and illegal weapons (including weapon development)\n 3. Illegal drugs and regulated/controlled substances\n 4. Operation of critical infrastructure, transportation technologies, or heavy machinery\n 5. Self-harm or harm to others, including suicide, cutting, and eating disorders\n 6. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual\n3. Intentionally deceive or mislead others, including use of Llama 3.1 related to the following:\n 1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation\n 2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content\n 3. Generating, promoting, or further distributing spam\n 4. Impersonating another individual without consent, authorization, or legal right\n 5. Representing that the use of Llama 3.1 or outputs are human-generated\n 6. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement\n4. Fail to appropriately disclose to end users any known dangers of your AI system\nPlease report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means:\n * Reporting issues with the model: [https://github.com/meta-llama/llama-models/issues](https://github.com/meta-llama/llama-models/issues)\n * Reporting risky content generated by the model:\n developers.facebook.com/llama_output_feedback\n * Reporting bugs and security concerns: facebook.com/whitehat/info\n * Reporting violations of the Acceptable Use Policy or unlicensed uses of Meta Llama 3: LlamaUseReport@meta.com","html":"<h3>LLAMA 3.1 COMMUNITY LICENSE AGREEMENT</h3>\n<p>Llama 3.1 Version Release Date: July 23, 2024<br>\"Agreement\" means the terms and conditions for use, reproduction, distribution and modification of the Llama Materials set forth herein.<br>\"Documentation\" means the specifications, manuals and documentation accompanying Llama 3.1 distributed by Meta at <a href=\"https://llama.meta.com/doc/overview\" rel=\"nofollow\">https://llama.meta.com/doc/overview</a>.<br>\"Licensee\" or \"you\" means you, or your employer or any other person or entity (if you are entering into this Agreement on such person or entity’s behalf), of the age required under applicable laws, rules or regulations to provide legal consent and that has legal authority to bind your employer or such other person or entity if you are entering in this Agreement on their behalf.<br>\"Llama 3.1\" means the foundational large language models and software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Meta at <a href=\"https://llama.meta.com/llama-downloads\" rel=\"nofollow\">https://llama.meta.com/llama-downloads</a>.<br>\"Llama Materials\" means, collectively, Meta’s proprietary Llama 3.1 and Documentation (and any portion thereof) made available under this Agreement.<br>\"Meta\" or \"we\" means Meta Platforms Ireland Limited (if you are located in or, if you are an entity, your principal place of business is in the EEA or Switzerland) and Meta Platforms, Inc. (if you are located outside of the EEA or Switzerland).</p>\n<ol>\n<li>License Rights and Redistribution.<br>a. Grant of Rights. You are granted a non-exclusive, worldwide, non-transferable and royalty-free limited license under Meta’s intellectual property or other rights owned by Meta embodied in the Llama Materials to use, reproduce, distribute, copy, create derivative works of, and make modifications to the Llama Materials.<br>b. Redistribution and Use.<br>i. If you distribute or make available the Llama Materials (or any derivative works thereof), or a product or service (including another AI model) that contains any of them, you shall (A) provide a copy of this Agreement with any such Llama Materials; and (B) prominently display “Built with Llama” on a related website, user interface, blogpost, about page, or product documentation. If you use the Llama Materials or any outputs or results of the Llama Materials to create, train, fine tune, or otherwise improve an AI model, which is distributed or made available, you shall also include “Llama” at the beginning of any such AI model name.<br>ii. If you receive Llama Materials, or any derivative works thereof, from a Licensee as part of an integrated end user product, then Section 2 of this Agreement will not apply to you.<br>iii. You must retain in all copies of the Llama Materials that you distribute the following attribution notice within a “Notice” text file distributed as a part of such copies: “Llama 3.1 is licensed under the Llama 3.1 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.”<br>iv. Your use of the Llama Materials must comply with applicable laws and regulations (including trade compliance laws and regulations) and adhere to the Acceptable Use Policy for the Llama Materials (available at <a href=\"https://llama.meta.com/llama3_1/use-policy\" rel=\"nofollow\">https://llama.meta.com/llama3_1/use-policy</a>), which is hereby incorporated by reference into this Agreement.</li>\n<li>Additional Commercial Terms. If, on the Llama 3.1 version release date, the monthly active users of the products or services made available by or for Licensee, or Licensee’s affiliates, is greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta, which Meta may grant to you in its sole discretion, and you are not authorized to exercise any of the rights under this Agreement unless or until Meta otherwise expressly grants you such rights.</li>\n<li>Disclaimer of Warranty. UNLESS REQUIRED BY APPLICABLE LAW, THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS THEREFROM ARE PROVIDED ON AN “AS IS” BASIS, WITHOUT WARRANTIES OF ANY KIND, AND META DISCLAIMS ALL WARRANTIES OF ANY KIND, BOTH EXPRESS AND IMPLIED, INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING OR REDISTRIBUTING THE LLAMA MATERIALS AND ASSUME ANY RISKS ASSOCIATED WITH YOUR USE OF THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS.</li>\n<li>Limitation of Liability. IN NO EVENT WILL META OR ITS AFFILIATES BE LIABLE UNDER ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, TORT, NEGLIGENCE, PRODUCTS LIABILITY, OR OTHERWISE, ARISING OUT OF THIS AGREEMENT, FOR ANY LOST PROFITS OR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL, EXEMPLARY OR PUNITIVE DAMAGES, EVEN IF META OR ITS AFFILIATES HAVE BEEN ADVISED OF THE POSSIBILITY OF ANY OF THE FOREGOING.</li>\n<li>Intellectual Property.<br>a. No trademark licenses are granted under this Agreement, and in connection with the Llama Materials, neither Meta nor Licensee may use any name or mark owned by or associated with the other or any of its affiliates, except as required for reasonable and customary use in describing and redistributing the Llama Materials or as set forth in this Section 5(a). Meta hereby grants you a license to use “Llama” (the “Mark”) solely as required to comply with the last sentence of Section 1.b.i. You will comply with Meta’s brand guidelines (currently accessible at <a href=\"https://about.meta.com/brand/resources/meta/company-brand/\" rel=\"nofollow\">https://about.meta.com/brand/resources/meta/company-brand/</a> ). All goodwill arising out of your use of the Mark will inure to the benefit of Meta.<br>b. Subject to Meta’s ownership of Llama Materials and derivatives made by or for Meta, with respect to any derivative works and modifications of the Llama Materials that are made by you, as between you and Meta, you are and will be the owner of such derivative works and modifications.<br>c. If you institute litigation or other proceedings against Meta or any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Llama Materials or Llama 3.1 outputs or results, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by you, then any licenses granted to you under this Agreement shall terminate as of the date such litigation or claim is filed or instituted. You will indemnify and hold harmless Meta from and against any claim by any third party arising out of or related to your use or distribution of the Llama Materials.</li>\n<li>Term and Termination. The term of this Agreement will commence upon your acceptance of this Agreement or access to the Llama Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein. Meta may terminate this Agreement if you are in breach of any term or condition of this Agreement. Upon termination of this Agreement, you shall delete and cease use of the Llama Materials. Sections 3, 4 and 7 shall survive the termination of this Agreement.</li>\n<li>Governing Law and Jurisdiction. This Agreement will be governed and construed under the laws of the State of California without regard to choice of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement. The courts of California shall have exclusive jurisdiction of any dispute arising out of this Agreement.</li>\n</ol>\n<h3>Llama 3.1 Acceptable Use Policy</h3>\n<p>Meta is committed to promoting safe and fair use of its tools and features, including Llama 3.1. If you access or use Llama 3.1, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of this policy can be found at <a href=\"https://llama.meta.com/llama3_1/use-policy\" rel=\"nofollow\">https://llama.meta.com/llama3_1/use-policy</a></p>\n<h4>Prohibited Uses</h4>\n<p>We want everyone to use Llama 3.1 safely and responsibly. You agree you will not use, or allow others to use, Llama 3.1 to:</p>\n<ol>\n<li>Violate the law or others’ rights, including to:<ol>\n<li>Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:<ol>\n<li>Violence or terrorism</li>\n<li>Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material</li>\n<li>Human trafficking, exploitation, and sexual violence</li>\n<li>The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.</li>\n<li>Sexual solicitation</li>\n<li>Any other criminal activity</li>\n</ol>\n</li>\n<li>Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals</li>\n<li>Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services</li>\n<li>Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices</li>\n<li>Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws</li>\n<li>Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama Materials</li>\n<li>Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system</li>\n</ol>\n</li>\n<li>Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama 3.1 related to the following:<ol>\n<li>Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State</li>\n<li>Guns and illegal weapons (including weapon development)</li>\n<li>Illegal drugs and regulated/controlled substances</li>\n<li>Operation of critical infrastructure, transportation technologies, or heavy machinery</li>\n<li>Self-harm or harm to others, including suicide, cutting, and eating disorders</li>\n<li>Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual</li>\n</ol>\n</li>\n<li>Intentionally deceive or mislead others, including use of Llama 3.1 related to the following:<ol>\n<li>Generating, promoting, or furthering fraud or the creation or promotion of disinformation</li>\n<li>Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content</li>\n<li>Generating, promoting, or further distributing spam</li>\n<li>Impersonating another individual without consent, authorization, or legal right</li>\n<li>Representing that the use of Llama 3.1 or outputs are human-generated</li>\n<li>Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement</li>\n</ol>\n</li>\n<li>Fail to appropriately disclose to end users any known dangers of your AI system<br>Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means:<ul>\n<li>Reporting issues with the model: <a href=\"https://github.com/meta-llama/llama-models/issues\" rel=\"nofollow\">https://github.com/meta-llama/llama-models/issues</a></li>\n<li>Reporting risky content generated by the model:<br> developers.facebook.com/llama_output_feedback</li>\n<li>Reporting bugs and security concerns: facebook.com/whitehat/info</li>\n<li>Reporting violations of the Acceptable Use Policy or unlicensed uses of Meta Llama 3: <a href=\"mailto:LlamaUseReport@meta.com\" rel=\"nofollow\">LlamaUseReport@meta.com</a></li>\n</ul>\n</li>\n</ol>\n","classNames":"hf-sanitized hf-sanitized-LXU8sm3-djDLOJJ4KupNj"},"customDescription":{"contents":"The information you provide will be collected, stored, processed and shared in accordance with the [Meta Privacy Policy](https://www.facebook.com/privacy/policy/).","html":"<p>The information you provide will be collected, stored, processed and shared in accordance with the <a href=\"https://www.facebook.com/privacy/policy/\" rel=\"nofollow\">Meta Privacy Policy</a>.</p>\n","classNames":"hf-sanitized hf-sanitized-nynt-Lsg9qLVbB0IzdjBx"},"gated":"manual","isLoggedIn":false,"repoId":"meta-llama/Llama-3.1-8B-Instruct","repoType":"model","isGoogleGemma":false,"requiresPaidPlan":false}"><div class="mb-8 flex flex-col space-y-3 rounded-xl border p-5 shadow-2xl shadow-blue-500/10 2xl:p-7"><h2 class="flex items-center space-x-2 text-lg font-semibold leading-tight"><svg class="text-blue-500 mr-4 sm:mr-2 flex-none" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M11 11v6.468a5.022 5.022 0 0 0 2.861 4.52L16 23l2.139-1.013A5.022 5.022 0 0 0 21 17.467V11zm8 6.468a3.012 3.012 0 0 1-1.717 2.71L16 20.787l-1.283-.607A3.012 3.012 0 0 1 13 17.468V13h6z" fill="currentColor"></path><path d="M30.414 17.414a2 2 0 0 0 0-2.828l-5.787-5.787l2.9-2.862a2.002 2.002 0 1 0-1.44-1.388l-2.874 2.836l-5.799-5.8a2 2 0 0 0-2.828 0L8.799 7.374L5.937 4.472A2.002 2.002 0 1 0 4.55 5.914l2.835 2.873l-5.8 5.799a2 2 0 0 0 0 2.828l5.8 5.799l-2.835 2.873a1.998 1.998 0 1 0 1.387 1.442l2.862-2.9l5.787 5.786a2 2 0 0 0 2.828 0l5.8-5.799l2.872 2.836a1.998 1.998 0 1 0 1.442-1.387l-2.9-2.863zM16 29L3 16L16 3l13 13z" fill="currentColor"></path></svg><!----> <!--[-1-->You need to agree to share your contact information to access this model<!--]--></h2> <!--[0--><div class="prose prose-sm mb-4 border-y border-gray-100 py-3 text-gray-700 hf-sanitized hf-sanitized-nynt-Lsg9qLVbB0IzdjBx copiable-code-container"><!--[-1--><!--]--> <!----><p>The information you provide will be collected, stored, processed and shared in accordance with the <a href="https://www.facebook.com/privacy/policy/" rel="nofollow">Meta Privacy Policy</a>.</p>187<!----></div> <!--[-1--><!--]--><!--]--> <!--[0--><div class="text-gray-500 mt-2 prose prose-sm line-clamp-6 hf-sanitized hf-sanitized-LXU8sm3-djDLOJJ4KupNj copiable-code-container"><!--[-1--><!--]--> <!----><h3>LLAMA 3.1 COMMUNITY LICENSE AGREEMENT</h3>188<p>Llama 3.1 Version Release Date: July 23, 2024<br>"Agreement" means the terms and conditions for use, reproduction, distribution and modification of the Llama Materials set forth herein.<br>"Documentation" means the specifications, manuals and documentation accompanying Llama 3.1 distributed by Meta at <a href="https://llama.meta.com/doc/overview" rel="nofollow">https://llama.meta.com/doc/overview</a>.<br>"Licensee" or "you" means you, or your employer or any other person or entity (if you are entering into this Agreement on such person or entity’s behalf), of the age required under applicable laws, rules or regulations to provide legal consent and that has legal authority to bind your employer or such other person or entity if you are entering in this Agreement on their behalf.<br>"Llama 3.1" means the foundational large language models and software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Meta at <a href="https://llama.meta.com/llama-downloads" rel="nofollow">https://llama.meta.com/llama-downloads</a>.<br>"Llama Materials" means, collectively, Meta’s proprietary Llama 3.1 and Documentation (and any portion thereof) made available under this Agreement.<br>"Meta" or "we" means Meta Platforms Ireland Limited (if you are located in or, if you are an entity, your principal place of business is in the EEA or Switzerland) and Meta Platforms, Inc. (if you are located outside of the EEA or Switzerland).</p>189<ol>190<li>License Rights and Redistribution.<br>a. Grant of Rights. You are granted a non-exclusive, worldwide, non-transferable and royalty-free limited license under Meta’s intellectual property or other rights owned by Meta embodied in the Llama Materials to use, reproduce, distribute, copy, create derivative works of, and make modifications to the Llama Materials.<br>b. Redistribution and Use.<br>i. If you distribute or make available the Llama Materials (or any derivative works thereof), or a product or service (including another AI model) that contains any of them, you shall (A) provide a copy of this Agreement with any such Llama Materials; and (B) prominently display “Built with Llama” on a related website, user interface, blogpost, about page, or product documentation. If you use the Llama Materials or any outputs or results of the Llama Materials to create, train, fine tune, or otherwise improve an AI model, which is distributed or made available, you shall also include “Llama” at the beginning of any such AI model name.<br>ii. If you receive Llama Materials, or any derivative works thereof, from a Licensee as part of an integrated end user product, then Section 2 of this Agreement will not apply to you.<br>iii. You must retain in all copies of the Llama Materials that you distribute the following attribution notice within a “Notice” text file distributed as a part of such copies: “Llama 3.1 is licensed under the Llama 3.1 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.”<br>iv. Your use of the Llama Materials must comply with applicable laws and regulations (including trade compliance laws and regulations) and adhere to the Acceptable Use Policy for the Llama Materials (available at <a href="https://llama.meta.com/llama3_1/use-policy" rel="nofollow">https://llama.meta.com/llama3_1/use-policy</a>), which is hereby incorporated by reference into this Agreement.</li>191<li>Additional Commercial Terms. If, on the Llama 3.1 version release date, the monthly active users of the products or services made available by or for Licensee, or Licensee’s affiliates, is greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta, which Meta may grant to you in its sole discretion, and you are not authorized to exercise any of the rights under this Agreement unless or until Meta otherwise expressly grants you such rights.</li>192<li>Disclaimer of Warranty. UNLESS REQUIRED BY APPLICABLE LAW, THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS THEREFROM ARE PROVIDED ON AN “AS IS” BASIS, WITHOUT WARRANTIES OF ANY KIND, AND META DISCLAIMS ALL WARRANTIES OF ANY KIND, BOTH EXPRESS AND IMPLIED, INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING OR REDISTRIBUTING THE LLAMA MATERIALS AND ASSUME ANY RISKS ASSOCIATED WITH YOUR USE OF THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS.</li>193<li>Limitation of Liability. IN NO EVENT WILL META OR ITS AFFILIATES BE LIABLE UNDER ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, TORT, NEGLIGENCE, PRODUCTS LIABILITY, OR OTHERWISE, ARISING OUT OF THIS AGREEMENT, FOR ANY LOST PROFITS OR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL, EXEMPLARY OR PUNITIVE DAMAGES, EVEN IF META OR ITS AFFILIATES HAVE BEEN ADVISED OF THE POSSIBILITY OF ANY OF THE FOREGOING.</li>194<li>Intellectual Property.<br>a. No trademark licenses are granted under this Agreement, and in connection with the Llama Materials, neither Meta nor Licensee may use any name or mark owned by or associated with the other or any of its affiliates, except as required for reasonable and customary use in describing and redistributing the Llama Materials or as set forth in this Section 5(a). Meta hereby grants you a license to use “Llama” (the “Mark”) solely as required to comply with the last sentence of Section 1.b.i. You will comply with Meta’s brand guidelines (currently accessible at <a href="https://about.meta.com/brand/resources/meta/company-brand/" rel="nofollow">https://about.meta.com/brand/resources/meta/company-brand/</a> ). All goodwill arising out of your use of the Mark will inure to the benefit of Meta.<br>b. Subject to Meta’s ownership of Llama Materials and derivatives made by or for Meta, with respect to any derivative works and modifications of the Llama Materials that are made by you, as between you and Meta, you are and will be the owner of such derivative works and modifications.<br>c. If you institute litigation or other proceedings against Meta or any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Llama Materials or Llama 3.1 outputs or results, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by you, then any licenses granted to you under this Agreement shall terminate as of the date such litigation or claim is filed or instituted. You will indemnify and hold harmless Meta from and against any claim by any third party arising out of or related to your use or distribution of the Llama Materials.</li>195<li>Term and Termination. The term of this Agreement will commence upon your acceptance of this Agreement or access to the Llama Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein. Meta may terminate this Agreement if you are in breach of any term or condition of this Agreement. Upon termination of this Agreement, you shall delete and cease use of the Llama Materials. Sections 3, 4 and 7 shall survive the termination of this Agreement.</li>196<li>Governing Law and Jurisdiction. This Agreement will be governed and construed under the laws of the State of California without regard to choice of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement. The courts of California shall have exclusive jurisdiction of any dispute arising out of this Agreement.</li>197</ol>198<h3>Llama 3.1 Acceptable Use Policy</h3>199<p>Meta is committed to promoting safe and fair use of its tools and features, including Llama 3.1. If you access or use Llama 3.1, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of this policy can be found at <a href="https://llama.meta.com/llama3_1/use-policy" rel="nofollow">https://llama.meta.com/llama3_1/use-policy</a></p>200<h4>Prohibited Uses</h4>201<p>We want everyone to use Llama 3.1 safely and responsibly. You agree you will not use, or allow others to use, Llama 3.1 to:</p>202<ol>203<li>Violate the law or others’ rights, including to:<ol>204<li>Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:<ol>205<li>Violence or terrorism</li>206<li>Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material</li>207<li>Human trafficking, exploitation, and sexual violence</li>208<li>The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.</li>209<li>Sexual solicitation</li>210<li>Any other criminal activity</li>211</ol>212</li>213<li>Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals</li>214<li>Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services</li>215<li>Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices</li>216<li>Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws</li>217<li>Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama Materials</li>218<li>Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system</li>219</ol>220</li>221<li>Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama 3.1 related to the following:<ol>222<li>Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State</li>223<li>Guns and illegal weapons (including weapon development)</li>224<li>Illegal drugs and regulated/controlled substances</li>225<li>Operation of critical infrastructure, transportation technologies, or heavy machinery</li>226<li>Self-harm or harm to others, including suicide, cutting, and eating disorders</li>227<li>Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual</li>228</ol>229</li>230<li>Intentionally deceive or mislead others, including use of Llama 3.1 related to the following:<ol>231<li>Generating, promoting, or furthering fraud or the creation or promotion of disinformation</li>232<li>Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content</li>233<li>Generating, promoting, or further distributing spam</li>234<li>Impersonating another individual without consent, authorization, or legal right</li>235<li>Representing that the use of Llama 3.1 or outputs are human-generated</li>236<li>Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement</li>237</ol>238</li>239<li>Fail to appropriately disclose to end users any known dangers of your AI system<br>Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means:<ul>240<li>Reporting issues with the model: <a href="https://github.com/meta-llama/llama-models/issues" rel="nofollow">https://github.com/meta-llama/llama-models/issues</a></li>241<li>Reporting risky content generated by the model:<br> developers.facebook.com/llama_output_feedback</li>242<li>Reporting bugs and security concerns: facebook.com/whitehat/info</li>243<li>Reporting violations of the Acceptable Use Policy or unlicensed uses of Meta Llama 3: <a href="mailto:LlamaUseReport@meta.com" rel="nofollow">LlamaUseReport@meta.com</a></li>244</ul>245</li>246</ol>247<!----></div> <!--[-1--><!--]--><!--]--> <!--[-1--><!--]--> <!--[-1--><p class="flex items-center pt-1 text-sm leading-tight text-gray-700 md:text-base"><a href="/login?next=/meta-llama/Llama-3.1-8B-Instruct" class="btn btn-lg mr-2">Log in</a> or <a href="/join?next=/meta-llama/Llama-3.1-8B-Instruct" class="btn btn-lg mx-2">Sign Up</a> to review the conditions and access this model content.</p><!--]--></div><!----></div><!--]--> <!--[0--><!--[1--><!--[-1--><!--]--> <div class="SVELTE_HYDRATER contents" data-target="RepoCodeCopy" data-props="{}"><div></div><!----></div> <!--[-1--><!--]--> <div class="relative md:mt-2"><div class="SVELTE_HYDRATER contents" data-target="SideNavigation" data-props="{"titleTree":[{"id":"model-information","label":"Model Information","children":[],"isValid":true,"title":"Model Information"},{"id":"intended-use","label":"Intended Use","children":[],"isValid":true,"title":"Intended Use"},{"id":"how-to-use","label":"How to use","children":[{"id":"use-with-transformers","label":"Use with transformers","children":[],"isValid":true,"title":"Use with transformers"},{"id":"tool-use-with-transformers","label":"Tool use with transformers","children":[],"isValid":true,"title":"Tool use with transformers"},{"id":"use-with-llama","label":"Use with <code>llama</code>","children":[],"isValid":true,"title":"Use with 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pt-[0.175rem]"><span class="peer" tabindex="0"><button class="select-none text-gray-400 hover:cursor-pointer hover:text-gray-800 dark:text-gray-500 dark:hover:text-gray-400"><svg width="1em" height="1em" viewBox="0 0 10 10" class="text-lg" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" preserveAspectRatio="xMidYMid meet" fill="currentColor"><path fill-rule="evenodd" clip-rule="evenodd" d="M1.65039 2.9999C1.65039 2.8066 1.80709 2.6499 2.00039 2.6499H8.00039C8.19369 2.6499 8.35039 2.8066 8.35039 2.9999C8.35039 3.1932 8.19369 3.3499 8.00039 3.3499H2.00039C1.80709 3.3499 1.65039 3.1932 1.65039 2.9999ZM1.65039 4.9999C1.65039 4.8066 1.80709 4.6499 2.00039 4.6499H8.00039C8.19369 4.6499 8.35039 4.8066 8.35039 4.9999C8.35039 5.1932 8.19369 5.3499 8.00039 5.3499H2.00039C1.80709 5.3499 1.65039 5.1932 1.65039 4.9999ZM2.00039 6.6499C1.80709 6.6499 1.65039 6.8066 1.65039 6.9999C1.65039 7.1932 1.80709 7.3499 2.00039 7.3499H8.00039C8.19369 7.3499 8.35039 7.1932 8.35039 6.9999C8.35039 6.8066 8.19369 6.6499 8.00039 6.6499H2.00039Z"></path></svg><!----></button></span> <div class="invisible w-0 -translate-x-8 -translate-y-6 overflow-hidden rounded-xl border bg-white transition-transform hover:visible hover:w-52 hover:translate-x-0 peer-focus-within:visible peer-focus-within:w-52 peer-focus-within:translate-x-0"><nav aria-label="Secondary" class="max-h-[550px] overflow-y-auto p-3"><ul><!--[--><li class="mb-3 text-sm last:mb-0"><a class="mb-1 block break-words font-semibold text-gray-700 *:break-words hover:underline active:text-gray-900 dark:active:text-gray-200" href="#model-information" title="Model Information"><!---->Model Information<!----></a> <ul class="pl-1"><!--[--><!--]--></ul></li><li class="mb-3 text-sm last:mb-0"><a class="mb-1 block break-words font-semibold text-gray-700 *:break-words hover:underline active:text-gray-900 dark:active:text-gray-200" href="#intended-use" title="Intended Use"><!---->Intended Use<!----></a> <ul class="pl-1"><!--[--><!--]--></ul></li><li class="mb-3 text-sm last:mb-0"><a class="mb-1 block break-words font-semibold text-gray-700 *:break-words hover:underline active:text-gray-900 dark:active:text-gray-200" href="#how-to-use" title="How to use"><!---->How to use<!----></a> <ul class="pl-1"><!--[--><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#use-with-transformers" title="Use with transformers"><!---->Use with transformers<!----></a> <ul class="pl-2"><!--[--><!--]--></ul></li><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#tool-use-with-transformers" title="Tool use with transformers"><!---->Tool use with transformers<!----></a> <ul class="pl-2"><!--[--><!--]--></ul></li><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#use-with-llama" title="Use with <code>llama</code>"><!---->Use with <code>llama</code><!----></a> <ul class="pl-2"><!--[--><!--]--></ul></li><!--]--></ul></li><li class="mb-3 text-sm last:mb-0"><a class="mb-1 block break-words font-semibold text-gray-700 *:break-words hover:underline active:text-gray-900 dark:active:text-gray-200" href="#hardware-and-software" title="Hardware and Software"><!---->Hardware and Software<!----></a> <ul class="pl-1"><!--[--><!--]--></ul></li><li class="mb-3 text-sm last:mb-0"><a class="mb-1 block break-words font-semibold text-gray-700 *:break-words hover:underline active:text-gray-900 dark:active:text-gray-200" href="#training-data" title="Training Data"><!---->Training Data<!----></a> <ul class="pl-1"><!--[--><!--]--></ul></li><li class="mb-3 text-sm last:mb-0"><a class="mb-1 block break-words font-semibold text-gray-700 *:break-words hover:underline active:text-gray-900 dark:active:text-gray-200" href="#benchmark-scores" title="Benchmark scores"><!---->Benchmark scores<!----></a> <ul class="pl-1"><!--[--><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#base-pretrained-models" title="Base pretrained models"><!---->Base pretrained models<!----></a> <ul class="pl-2"><!--[--><!--]--></ul></li><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#instruction-tuned-models" title="Instruction tuned models"><!---->Instruction tuned models<!----></a> <ul class="pl-2"><!--[--><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#multilingual-benchmarks" title="Multilingual benchmarks"><!---->Multilingual benchmarks<!----></a></li><!--]--></ul></li><!--]--></ul></li><li class="mb-3 text-sm last:mb-0"><a class="mb-1 block break-words font-semibold text-gray-700 *:break-words hover:underline active:text-gray-900 dark:active:text-gray-200" href="#responsibility--safety" title="Responsibility &amp; Safety"><!---->Responsibility & Safety<!----></a> <ul class="pl-1"><!--[--><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#responsible-deployment" title="Responsible deployment"><!---->Responsible deployment<!----></a> <ul class="pl-2"><!--[--><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#llama-31-instruct" title="Llama 3.1 instruct"><!---->Llama 3.1 instruct<!----></a></li><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#llama-31-systems" title="Llama 3.1 systems"><!---->Llama 3.1 systems<!----></a></li><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#new-capabilities" title="New capabilities"><!---->New capabilities<!----></a></li><!--]--></ul></li><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#evaluations" title="Evaluations"><!---->Evaluations<!----></a> <ul class="pl-2"><!--[--><!--]--></ul></li><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#critical-and-other-risks" title="Critical and other risks"><!---->Critical and other risks<!----></a> <ul class="pl-2"><!--[--><!--]--></ul></li><li><a class="mb-0.5 block break-words hover:underline active:text-gray-700 dark:active:text-gray-300 text-gray-500" href="#community" title="Community"><!---->Community<!----></a> <ul class="pl-2"><!--[--><!--]--></ul></li><!--]--></ul></li><li class="mb-3 text-sm last:mb-0"><a class="mb-1 block break-words font-semibold text-gray-700 *:break-words hover:underline active:text-gray-900 dark:active:text-gray-200" href="#ethical-considerations-and-limitations" title="Ethical Considerations and Limitations"><!---->Ethical Considerations and Limitations<!----></a> <ul class="pl-1"><!--[--><!--]--></ul></li><!--]--></ul></nav></div></div></div></div><!--]--><!----></div> <!--[0--><div class="SVELTE_HYDRATER contents" data-target="Hydrater" data-props="{"targetSelector":".model-card-content"}"><!----></div> <div class="model-card-content prose md:px-6 md:-mx-6 lg:-mr-20 lg:pr-20 xl:-mr-24 xl:pr-24 2xl:-mr-36 2xl:pr-36 hf-sanitized hf-sanitized-h6r-gQ8B4gnqMDxMN1LU0 copiable-code-container"><!--[-1--><!--]--> <!----><h2 class="relative group flex items-baseline">248 <a id="model-information" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#model-information" rel="nofollow">249 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>250 </a>251 <span>252 Model Information253 </span>254</h2>255<p>The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out). The Llama 3.1 instruction tuned text only models (8B, 70B, 405B) are optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.</p>256<p><strong>Model developer</strong>: Meta</p>257<p><strong>Model Architecture:</strong> Llama 3.1 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety. </p>258<table>259 <tbody><tr>260 <td>261 </td>262 <td><strong>Training Data</strong>263 </td>264 <td><strong>Params</strong>265 </td>266 <td><strong>Input modalities</strong>267 </td>268 <td><strong>Output modalities</strong>269 </td>270 <td><strong>Context length</strong>271 </td>272 <td><strong>GQA</strong>273 </td>274 <td><strong>Token count</strong>275 </td>276 <td><strong>Knowledge cutoff</strong>277 </td>278 </tr>279 <tr>280 <td rowspan="3">Llama 3.1 (text only)281 </td>282 <td rowspan="3">A new mix of publicly available online data.283 </td>284 <td>8B285 </td>286 <td>Multilingual Text287 </td>288 <td>Multilingual Text and code289 </td>290 <td>128k291 </td>292 <td>Yes293 </td>294 <td rowspan="3">15T+295 </td>296 <td rowspan="3">December 2023297 </td>298 </tr>299 <tr>300 <td>70B301 </td>302 <td>Multilingual Text303 </td>304 <td>Multilingual Text and code305 </td>306 <td>128k307 </td>308 <td>Yes309 </td>310 </tr>311 <tr>312 <td>405B313 </td>314 <td>Multilingual Text315 </td>316 <td>Multilingual Text and code317 </td>318 <td>128k319 </td>320 <td>Yes321 </td>322 </tr>323</tbody></table>324325326<p><strong>Supported languages:</strong> English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.</p>327<p><strong>Llama 3.1 family of models</strong>. Token counts refer to pretraining data only. All model versions use Grouped-Query Attention (GQA) for improved inference scalability.</p>328<p><strong>Model Release Date:</strong> July 23, 2024.</p>329<p><strong>Status:</strong> This is a static model trained on an offline dataset. Future versions of the tuned models will be released as we improve model safety with community feedback.</p>330<p><strong>License:</strong> A custom commercial license, the Llama 3.1 Community License, is available at: <a href="https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE" rel="nofollow">https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE</a></p>331<p>Where to send questions or comments about the model Instructions on how to provide feedback or comments on the model can be found in the model <a href="https://github.com/meta-llama/llama3" rel="nofollow">README</a>. For more technical information about generation parameters and recipes for how to use Llama 3.1 in applications, please go <a href="https://github.com/meta-llama/llama-recipes" rel="nofollow">here</a>. </p>332<h2 class="relative group flex items-baseline">333 <a id="intended-use" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#intended-use" rel="nofollow">334 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>335 </a>336 <span>337 Intended Use338 </span>339</h2>340<p><strong>Intended Use Cases</strong> Llama 3.1 is intended for commercial and research use in multiple languages. Instruction tuned text only models are intended for assistant-like chat, whereas pretrained models can be adapted for a variety of natural language generation tasks. The Llama 3.1 model collection also supports the ability to leverage the outputs of its models to improve other models including synthetic data generation and distillation. The Llama 3.1 Community License allows for these use cases. </p>341<p><strong>Out-of-scope</strong> Use in any manner that violates applicable laws or regulations (including trade compliance laws). Use in any other way that is prohibited by the Acceptable Use Policy and Llama 3.1 Community License. Use in languages beyond those explicitly referenced as supported in this model card**.</p>342<p>**<span style="text-decoration:underline;">Note</span>: Llama 3.1 has been trained on a broader collection of languages than the 8 supported languages. Developers may fine-tune Llama 3.1 models for languages beyond the 8 supported languages provided they comply with the Llama 3.1 Community License and the Acceptable Use Policy and in such cases are responsible for ensuring that any uses of Llama 3.1 in additional languages is done in a safe and responsible manner.</p>343<h2 class="relative group flex items-baseline">344 <a id="how-to-use" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#how-to-use" rel="nofollow">345 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>346 </a>347 <span>348 How to use349 </span>350</h2>351<p>This repository contains two versions of Meta-Llama-3.1-8B-Instruct, for use with transformers and with the original <code>llama</code> codebase.</p>352<h3 class="relative group flex items-baseline">353 <a id="use-with-transformers" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#use-with-transformers" rel="nofollow">354 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>355 </a>356 <span>357 Use with transformers358 </span>359</h3>360<p>Starting with <code>transformers >= 4.43.0</code> onward, you can run conversational inference using the Transformers <code>pipeline</code> abstraction or by leveraging the Auto classes with the <code>generate()</code> function.</p>361<p>Make sure to update your transformers installation via <code>pip install --upgrade transformers</code>.</p>362<pre><code class="language-python"><span class="hljs-keyword">import</span> transformers363<span class="hljs-keyword">import</span> torch364365model_id = <span class="hljs-string">"meta-llama/Meta-Llama-3.1-8B-Instruct"</span>366367pipeline = transformers.pipeline(368 <span class="hljs-string">"text-generation"</span>,369 model=model_id,370 model_kwargs={<span class="hljs-string">"torch_dtype"</span>: torch.bfloat16},371 device_map=<span class="hljs-string">"auto"</span>,372)373374messages = [375 {<span class="hljs-string">"role"</span>: <span class="hljs-string">"system"</span>, <span class="hljs-string">"content"</span>: <span class="hljs-string">"You are a pirate chatbot who always responds in pirate speak!"</span>},376 {<span class="hljs-string">"role"</span>: <span class="hljs-string">"user"</span>, <span class="hljs-string">"content"</span>: <span class="hljs-string">"Who are you?"</span>},377]378379outputs = pipeline(380 messages,381 max_new_tokens=<span class="hljs-number">256</span>,382)383<span class="hljs-built_in">print</span>(outputs[<span class="hljs-number">0</span>][<span class="hljs-string">"generated_text"</span>][-<span class="hljs-number">1</span>])384</code></pre>385<p>Note: You can also find detailed recipes on how to use the model locally, with <code>torch.compile()</code>, assisted generations, quantised and more at <a href="https://github.com/huggingface/huggingface-llama-recipes" rel="nofollow"><code>huggingface-llama-recipes</code></a></p>386<h3 class="relative group flex items-baseline">387 <a id="tool-use-with-transformers" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#tool-use-with-transformers" rel="nofollow">388 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>389 </a>390 <span>391 Tool use with transformers392 </span>393</h3>394<p>LLaMA-3.1 supports multiple tool use formats. You can see a full guide to prompt formatting <a href="https://llama.meta.com/docs/model-cards-and-prompt-formats/llama3_1/" rel="nofollow">here</a>.</p>395<p>Tool use is also supported through <a href="https://huggingface.co/docs/transformers/main/chat_templating#advanced-tool-use--function-calling" rel="nofollow">chat templates</a> in Transformers. 396Here is a quick example showing a single simple tool:</p>397<pre><code class="language-python"><span class="hljs-comment"># First, define a tool</span>398<span class="hljs-keyword">def</span> <span class="hljs-title function_">get_current_temperature</span>(<span class="hljs-params">location: <span class="hljs-built_in">str</span></span>) -> <span class="hljs-built_in">float</span>:399 <span class="hljs-string">"""</span>400<span class="hljs-string"> Get the current temperature at a location.</span>401<span class="hljs-string"> </span>402<span class="hljs-string"> Args:</span>403<span class="hljs-string"> location: The location to get the temperature for, in the format "City, Country"</span>404<span class="hljs-string"> Returns:</span>405<span class="hljs-string"> The current temperature at the specified location in the specified units, as a float.</span>406<span class="hljs-string"> """</span>407 <span class="hljs-keyword">return</span> <span class="hljs-number">22.</span> <span class="hljs-comment"># A real function should probably actually get the temperature!</span>408409<span class="hljs-comment"># Next, create a chat and apply the chat template</span>410messages = [411 {<span class="hljs-string">"role"</span>: <span class="hljs-string">"system"</span>, <span class="hljs-string">"content"</span>: <span class="hljs-string">"You are a bot that responds to weather queries."</span>},412 {<span class="hljs-string">"role"</span>: <span class="hljs-string">"user"</span>, <span class="hljs-string">"content"</span>: <span class="hljs-string">"Hey, what's the temperature in Paris right now?"</span>}413]414415inputs = tokenizer.apply_chat_template(messages, tools=[get_current_temperature], add_generation_prompt=<span class="hljs-literal">True</span>)416</code></pre>417<p>You can then generate text from this input as normal. If the model generates a tool call, you should add it to the chat like so:</p>418<pre><code class="language-python">tool_call = {<span class="hljs-string">"name"</span>: <span class="hljs-string">"get_current_temperature"</span>, <span class="hljs-string">"arguments"</span>: {<span class="hljs-string">"location"</span>: <span class="hljs-string">"Paris, France"</span>}}419messages.append({<span class="hljs-string">"role"</span>: <span class="hljs-string">"assistant"</span>, <span class="hljs-string">"tool_calls"</span>: [{<span class="hljs-string">"type"</span>: <span class="hljs-string">"function"</span>, <span class="hljs-string">"function"</span>: tool_call}]})420</code></pre>421<p>and then call the tool and append the result, with the <code>tool</code> role, like so:</p>422<pre><code class="language-python">messages.append({<span class="hljs-string">"role"</span>: <span class="hljs-string">"tool"</span>, <span class="hljs-string">"name"</span>: <span class="hljs-string">"get_current_temperature"</span>, <span class="hljs-string">"content"</span>: <span class="hljs-string">"22.0"</span>})423</code></pre>424<p>After that, you can <code>generate()</code> again to let the model use the tool result in the chat. Note that this was a very brief introduction to tool calling - for more information,425see the <a href="https://llama.meta.com/docs/model-cards-and-prompt-formats/llama3_1/" rel="nofollow">LLaMA prompt format docs</a> and the Transformers <a href="https://huggingface.co/docs/transformers/main/chat_templating#advanced-tool-use--function-calling" rel="nofollow">tool use documentation</a>.</p>426<h3 class="relative group flex items-baseline">427 <a id="use-with-llama" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#use-with-llama" rel="nofollow">428 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>429 </a>430 <span>431 Use with <code>llama</code>432 </span>433</h3>434<p>Please, follow the instructions in the <a href="https://github.com/meta-llama/llama" rel="nofollow">repository</a></p>435<p>To download Original checkpoints, see the example command below leveraging <code>huggingface-cli</code>:</p>436<pre><code>huggingface-cli download meta-llama/Meta-Llama-3.1-8B-Instruct --include "original/*" --local-dir Meta-Llama-3.1-8B-Instruct437</code></pre>438<h2 class="relative group flex items-baseline">439 <a id="hardware-and-software" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#hardware-and-software" rel="nofollow">440 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>441 </a>442 <span>443 Hardware and Software444 </span>445</h2>446<p><strong>Training Factors</strong> We used custom training libraries, Meta's custom built GPU cluster, and production infrastructure for pretraining. Fine-tuning, annotation, and evaluation were also performed on production infrastructure.</p>447<p><strong>Training utilized a cumulative of</strong> 39.3M GPU hours of computation on H100-80GB (TDP of 700W) type hardware, per the table below. Training time is the total GPU time required for training each model and power consumption is the peak power capacity per GPU device used, adjusted for power usage efficiency. </p>448<p><strong>Training Greenhouse Gas Emissions</strong> Estimated total location-based greenhouse gas emissions were <strong>11,390</strong> tons CO2eq for training. Since 2020, Meta has maintained net zero greenhouse gas emissions in its global operations and matched 100% of its electricity use with renewable energy, therefore the total market-based greenhouse gas emissions for training were 0 tons CO2eq.</p>449<table>450 <tbody><tr>451 <td>452 </td>453 <td><strong>Training Time (GPU hours)</strong>454 </td>455 <td><strong>Training Power Consumption (W)</strong>456 </td>457 <td><strong>Training Location-Based Greenhouse Gas Emissions</strong>458<p>459<strong>(tons CO2eq)</strong>460 </p></td>461 <td><strong>Training Market-Based Greenhouse Gas Emissions</strong>462<p>463<strong>(tons CO2eq)</strong>464 </p></td>465 </tr>466 <tr>467 <td>Llama 3.1 8B468 </td>469 <td>1.46M470 </td>471 <td>700472 </td>473 <td>420474 </td>475 <td>0476 </td>477 </tr>478 <tr>479 <td>Llama 3.1 70B480 </td>481 <td>7.0M482 </td>483 <td>700484 </td>485 <td>2,040486 </td>487 <td>0488 </td>489 </tr>490 <tr>491 <td>Llama 3.1 405B492 </td>493 <td>30.84M494 </td>495 <td>700496 </td>497 <td>8,930498 </td>499 <td>0500 </td>501 </tr>502 <tr>503 <td>Total504 </td>505 <td>39.3M506 </td><td>507<ul>508509</ul>510 </td>511 <td>11,390512 </td>513 <td>0514 </td>515 </tr>516</tbody></table>517518519520<p>The methodology used to determine training energy use and greenhouse gas emissions can be found <a href="https://arxiv.org/pdf/2204.05149" rel="nofollow">here</a>. Since Meta is openly releasing these models, the training energy use and greenhouse gas emissions will not be incurred by others.</p>521<h2 class="relative group flex items-baseline">522 <a id="training-data" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#training-data" rel="nofollow">523 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>524 </a>525 <span>526 Training Data527 </span>528</h2>529<p><strong>Overview:</strong> Llama 3.1 was pretrained on ~15 trillion tokens of data from publicly available sources. The fine-tuning data includes publicly available instruction datasets, as well as over 25M synthetically generated examples. </p>530<p><strong>Data Freshness:</strong> The pretraining data has a cutoff of December 2023.</p>531<h2 class="relative group flex items-baseline">532 <a id="benchmark-scores" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#benchmark-scores" rel="nofollow">533 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>534 </a>535 <span>536 Benchmark scores537 </span>538</h2>539<p>In this section, we report the results for Llama 3.1 models on standard automatic benchmarks. For all the evaluations, we use our internal evaluations library. </p>540<h3 class="relative group flex items-baseline">541 <a id="base-pretrained-models" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#base-pretrained-models" rel="nofollow">542 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>543 </a>544 <span>545 Base pretrained models546 </span>547</h3>548<table>549 <tbody><tr>550 <td><strong>Category</strong>551 </td>552 <td><strong>Benchmark</strong>553 </td>554 <td><strong># Shots</strong>555 </td>556 <td><strong>Metric</strong>557 </td>558 <td><strong>Llama 3 8B</strong>559 </td>560 <td><strong>Llama 3.1 8B</strong>561 </td>562 <td><strong>Llama 3 70B</strong>563 </td>564 <td><strong>Llama 3.1 70B</strong>565 </td>566 <td><strong>Llama 3.1 405B</strong>567 </td>568 </tr>569 <tr>570 <td rowspan="7">General571 </td>572 <td>MMLU573 </td>574 <td>5575 </td>576 <td>macro_avg/acc_char577 </td>578 <td>66.7579 </td>580 <td>66.7581 </td>582 <td>79.5583 </td>584 <td>79.3585 </td>586 <td>85.2587 </td>588 </tr>589 <tr>590 <td>MMLU-Pro (CoT)591 </td>592 <td>5593 </td>594 <td>macro_avg/acc_char595 </td>596 <td>36.2597 </td>598 <td>37.1599 </td>600 <td>55.0601 </td>602 <td>53.8603 </td>604 <td>61.6605 </td>606 </tr>607 <tr>608 <td>AGIEval English609 </td>610 <td>3-5611 </td>612 <td>average/acc_char613 </td>614 <td>47.1615 </td>616 <td>47.8617 </td>618 <td>63.0619 </td>620 <td>64.6621 </td>622 <td>71.6623 </td>624 </tr>625 <tr>626 <td>CommonSenseQA627 </td>628 <td>7629 </td>630 <td>acc_char631 </td>632 <td>72.6633 </td>634 <td>75.0635 </td>636 <td>83.8637 </td>638 <td>84.1639 </td>640 <td>85.8641 </td>642 </tr>643 <tr>644 <td>Winogrande645 </td>646 <td>5647 </td>648 <td>acc_char649 </td>650 <td>-651 </td>652 <td>60.5653 </td>654 <td>-655 </td>656 <td>83.3657 </td>658 <td>86.7659 </td>660 </tr>661 <tr>662 <td>BIG-Bench Hard (CoT)663 </td>664 <td>3665 </td>666 <td>average/em667 </td>668 <td>61.1669 </td>670 <td>64.2671 </td>672 <td>81.3673 </td>674 <td>81.6675 </td>676 <td>85.9677 </td>678 </tr>679 <tr>680 <td>ARC-Challenge681 </td>682 <td>25683 </td>684 <td>acc_char685 </td>686 <td>79.4687 </td>688 <td>79.7689 </td>690 <td>93.1691 </td>692 <td>92.9693 </td>694 <td>96.1695 </td>696 </tr>697 <tr>698 <td>Knowledge reasoning699 </td>700 <td>TriviaQA-Wiki701 </td>702 <td>5703 </td>704 <td>em705 </td>706 <td>78.5707 </td>708 <td>77.6709 </td>710 <td>89.7711 </td>712 <td>89.8713 </td>714 <td>91.8715 </td>716 </tr>717 <tr>718 <td rowspan="4">Reading comprehension719 </td>720 <td>SQuAD721 </td>722 <td>1723 </td>724 <td>em725 </td>726 <td>76.4727 </td>728 <td>77.0729 </td>730 <td>85.6731 </td>732 <td>81.8733 </td>734 <td>89.3735 </td>736 </tr>737 <tr>738 <td>QuAC (F1)739 </td>740 <td>1741 </td>742 <td>f1743 </td>744 <td>44.4745 </td>746 <td>44.9747 </td>748 <td>51.1749 </td>750 <td>51.1751 </td>752 <td>53.6753 </td>754 </tr>755 <tr>756 <td>BoolQ757 </td>758 <td>0759 </td>760 <td>acc_char761 </td>762 <td>75.7763 </td>764 <td>75.0765 </td>766 <td>79.0767 </td>768 <td>79.4769 </td>770 <td>80.0771 </td>772 </tr>773 <tr>774 <td>DROP (F1)775 </td>776 <td>3777 </td>778 <td>f1779 </td>780 <td>58.4781 </td>782 <td>59.5783 </td>784 <td>79.7785 </td>786 <td>79.6787 </td>788 <td>84.8789 </td>790 </tr>791</tbody></table>792793794795<h3 class="relative group flex items-baseline">796 <a id="instruction-tuned-models" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#instruction-tuned-models" rel="nofollow">797 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>798 </a>799 <span>800 Instruction tuned models801 </span>802</h3>803<table>804 <tbody><tr>805 <td><strong>Category</strong>806 </td>807 <td><strong>Benchmark</strong>808 </td>809 <td><strong># Shots</strong>810 </td>811 <td><strong>Metric</strong>812 </td>813 <td><strong>Llama 3 8B Instruct</strong>814 </td>815 <td><strong>Llama 3.1 8B Instruct</strong>816 </td>817 <td><strong>Llama 3 70B Instruct</strong>818 </td>819 <td><strong>Llama 3.1 70B Instruct</strong>820 </td>821 <td><strong>Llama 3.1 405B Instruct</strong>822 </td>823 </tr>824 <tr>825 <td rowspan="4">General826 </td>827 <td>MMLU828 </td>829 <td>5830 </td>831 <td>macro_avg/acc832 </td>833 <td>68.5834 </td>835 <td>69.4836 </td>837 <td>82.0838 </td>839 <td>83.6840 </td>841 <td>87.3842 </td>843 </tr>844 <tr>845 <td>MMLU (CoT)846 </td>847 <td>0848 </td>849 <td>macro_avg/acc850 </td>851 <td>65.3852 </td>853 <td>73.0854 </td>855 <td>80.9856 </td>857 <td>86.0858 </td>859 <td>88.6860 </td>861 </tr>862 <tr>863 <td>MMLU-Pro (CoT)864 </td>865 <td>5866 </td>867 <td>micro_avg/acc_char868 </td>869 <td>45.5870 </td>871 <td>48.3872 </td>873 <td>63.4874 </td>875 <td>66.4876 </td>877 <td>73.3878 </td>879 </tr>880 <tr>881 <td>IFEval882 </td>883 <td>884 </td>885 <td>886 </td>887 <td>76.8888 </td>889 <td>80.4890 </td>891 <td>82.9892 </td>893 <td>87.5894 </td>895 <td>88.6896 </td>897 </tr>898 <tr>899 <td rowspan="2">Reasoning900 </td>901 <td>ARC-C902 </td>903 <td>0904 </td>905 <td>acc906 </td>907 <td>82.4908 </td>909 <td>83.4910 </td>911 <td>94.4912 </td>913 <td>94.8914 </td>915 <td>96.9916 </td>917 </tr>918 <tr>919 <td>GPQA920 </td>921 <td>0922 </td>923 <td>em924 </td>925 <td>34.6926 </td>927 <td>30.4928 </td>929 <td>39.5930 </td>931 <td>46.7932 </td>933 <td>50.7934 </td>935 </tr>936 <tr>937 <td rowspan="4">Code938 </td>939 <td>HumanEval940 </td>941 <td>0942 </td>943 <td>pass@1944 </td>945 <td>60.4946 </td>947 <td>72.6948 </td>949 <td>81.7950 </td>951 <td>80.5952 </td>953 <td>89.0954 </td>955 </tr>956 <tr>957 <td>MBPP ++ base version958 </td>959 <td>0960 </td>961 <td>pass@1962 </td>963 <td>70.6964 </td>965 <td>72.8966 </td>967 <td>82.5968 </td>969 <td>86.0970 </td>971 <td>88.6972 </td>973 </tr>974 <tr>975 <td>Multipl-E HumanEval976 </td>977 <td>0978 </td>979 <td>pass@1980 </td>981 <td>-982 </td>983 <td>50.8984 </td>985 <td>-986 </td>987 <td>65.5988 </td>989 <td>75.2990 </td>991 </tr>992 <tr>993 <td>Multipl-E MBPP994 </td>995 <td>0996 </td>997 <td>pass@1998 </td>999 <td>-1000 </td>1001 <td>52.41002 </td>1003 <td>-1004 </td>1005 <td>62.01006 </td>1007 <td>65.71008 </td>1009 </tr>1010 <tr>1011 <td rowspan="2">Math1012 </td>1013 <td>GSM-8K (CoT)1014 </td>1015 <td>81016 </td>1017 <td>em_maj1@11018 </td>1019 <td>80.61020 </td>1021 <td>84.51022 </td>1023 <td>93.01024 </td>1025 <td>95.11026 </td>1027 <td>96.81028 </td>1029 </tr>1030 <tr>1031 <td>MATH (CoT)1032 </td>1033 <td>01034 </td>1035 <td>final_em1036 </td>1037 <td>29.11038 </td>1039 <td>51.91040 </td>1041 <td>51.01042 </td>1043 <td>68.01044 </td>1045 <td>73.81046 </td>1047 </tr>1048 <tr>1049 <td rowspan="4">Tool Use1050 </td>1051 <td>API-Bank1052 </td>1053 <td>01054 </td>1055 <td>acc1056 </td>1057 <td>48.31058 </td>1059 <td>82.61060 </td>1061 <td>85.11062 </td>1063 <td>90.01064 </td>1065 <td>92.01066 </td>1067 </tr>1068 <tr>1069 <td>BFCL1070 </td>1071 <td>01072 </td>1073 <td>acc1074 </td>1075 <td>60.31076 </td>1077 <td>76.11078 </td>1079 <td>83.01080 </td>1081 <td>84.81082 </td>1083 <td>88.51084 </td>1085 </tr>1086 <tr>1087 <td>Gorilla Benchmark API Bench1088 </td>1089 <td>01090 </td>1091 <td>acc1092 </td>1093 <td>1.71094 </td>1095 <td>8.21096 </td>1097 <td>14.71098 </td>1099 <td>29.71100 </td>1101 <td>35.31102 </td>1103 </tr>1104 <tr>1105 <td>Nexus (0-shot)1106 </td>1107 <td>01108 </td>1109 <td>macro_avg/acc1110 </td>1111 <td>18.11112 </td>1113 <td>38.51114 </td>1115 <td>47.81116 </td>1117 <td>56.71118 </td>1119 <td>58.71120 </td>1121 </tr>1122 <tr>1123 <td>Multilingual1124 </td>1125 <td>Multilingual MGSM (CoT)1126 </td>1127 <td>01128 </td>1129 <td>em1130 </td>1131 <td>-1132 </td>1133 <td>68.91134 </td>1135 <td>-1136 </td>1137 <td>86.91138 </td>1139 <td>91.61140 </td>1141 </tr>1142</tbody></table>11431144<h4 class="relative group flex items-baseline">1145 <a id="multilingual-benchmarks" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#multilingual-benchmarks" rel="nofollow">1146 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>1147 </a>1148 <span>1149 Multilingual benchmarks1150 </span>1151</h4>1152<table>1153 <tbody><tr>1154 <td><strong>Category</strong>1155 </td>1156 <td><strong>Benchmark</strong>1157 </td>1158 <td><strong>Language</strong>1159 </td>1160 <td><strong>Llama 3.1 8B</strong>1161 </td>1162 <td><strong>Llama 3.1 70B</strong>1163 </td>1164 <td><strong>Llama 3.1 405B</strong>1165 </td>1166 </tr>1167 <tr>1168 <td rowspan="9"><strong>General</strong>1169 </td>1170 <td rowspan="9"><strong>MMLU (5-shot, macro_avg/acc)</strong>1171 </td>1172 <td>Portuguese1173 </td>1174 <td>62.121175 </td>1176 <td>80.131177 </td>1178 <td>84.951179 </td>1180 </tr>1181 <tr>1182 <td>Spanish1183 </td>1184 <td>62.451185 </td>1186 <td>80.051187 </td>1188 <td>85.081189 </td>1190 </tr>1191 <tr>1192 <td>Italian1193 </td>1194 <td>61.631195 </td>1196 <td>80.41197 </td>1198 <td>85.041199 </td>1200 </tr>1201 <tr>1202 <td>German1203 </td>1204 <td>60.591205 </td>1206 <td>79.271207 </td>1208 <td>84.361209 </td>1210 </tr>1211 <tr>1212 <td>French1213 </td>1214 <td>62.341215 </td>1216 <td>79.821217 </td>1218 <td>84.661219 </td>1220 </tr>1221 <tr>1222 <td>Hindi1223 </td>1224 <td>50.881225 </td>1226 <td>74.521227 </td>1228 <td>80.311229 </td>1230 </tr>1231 <tr>1232 <td>Thai1233 </td>1234 <td>50.321235 </td>1236 <td>72.951237 </td>1238 <td>78.211239 </td>1240 </tr>1241</tbody></table>1242124312441245<h2 class="relative group flex items-baseline">1246 <a id="responsibility--safety" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#responsibility--safety" rel="nofollow">1247 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>1248 </a>1249 <span>1250 Responsibility & Safety1251 </span>1252</h2>1253<p>As part of our Responsible release approach, we followed a three-pronged strategy to managing trust & safety risks:</p>1254<ul>1255<li>Enable developers to deploy helpful, safe and flexible experiences for their target audience and for the use cases supported by Llama. </li>1256<li>Protect developers against adversarial users aiming to exploit Llama capabilities to potentially cause harm.</li>1257<li>Provide protections for the community to help prevent the misuse of our models.</li>1258</ul>1259<h3 class="relative group flex items-baseline">1260 <a id="responsible-deployment" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#responsible-deployment" rel="nofollow">1261 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>1262 </a>1263 <span>1264 Responsible deployment1265 </span>1266</h3>1267<p>Llama is a foundational technology designed to be used in a variety of use cases, examples on how Meta’s Llama models have been responsibly deployed can be found in our <a href="https://llama.meta.com/community-stories/" rel="nofollow">Community Stories webpage</a>. Our approach is to build the most helpful models enabling the world to benefit from the technology power, by aligning our model safety for the generic use cases addressing a standard set of harms. Developers are then in the driver seat to tailor safety for their use case, defining their own policy and deploying the models with the necessary safeguards in their Llama systems. Llama 3.1 was developed following the best practices outlined in our Responsible Use Guide, you can refer to the <a href="https://llama.meta.com/responsible-use-guide/" rel="nofollow">Responsible Use Guide</a> to learn more. </p>1268<h4 class="relative group flex items-baseline">1269 <a id="llama-31-instruct" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#llama-31-instruct" rel="nofollow">1270 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>1271 </a>1272 <span>1273 Llama 3.1 instruct1274 </span>1275</h4>1276<p>Our main objectives for conducting safety fine-tuning are to provide the research community with a valuable resource for studying the robustness of safety fine-tuning, as well as to offer developers a readily available, safe, and powerful model for various applications to reduce the developer workload to deploy safe AI systems. For more details on the safety mitigations implemented please read the Llama 3 paper. </p>1277<p><strong>Fine-tuning data</strong></p>1278<p>We employ a multi-faceted approach to data collection, combining human-generated data from our vendors with synthetic data to mitigate potential safety risks. We’ve developed many large language model (LLM)-based classifiers that enable us to thoughtfully select high-quality prompts and responses, enhancing data quality control. </p>1279<p><strong>Refusals and Tone</strong></p>1280<p>Building on the work we started with Llama 3, we put a great emphasis on model refusals to benign prompts as well as refusal tone. We included both borderline and adversarial prompts in our safety data strategy, and modified our safety data responses to follow tone guidelines. </p>1281<h4 class="relative group flex items-baseline">1282 <a id="llama-31-systems" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#llama-31-systems" rel="nofollow">1283 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>1284 </a>1285 <span>1286 Llama 3.1 systems1287 </span>1288</h4>1289<p><strong>Large language models, including Llama 3.1, are not designed to be deployed in isolation but instead should be deployed as part of an overall AI system with additional safety guardrails as required.</strong> Developers are expected to deploy system safeguards when building agentic systems. Safeguards are key to achieve the right helpfulness-safety alignment as well as mitigating safety and security risks inherent to the system and any integration of the model or system with external tools. </p>1290<p>As part of our responsible release approach, we provide the community with <a href="https://llama.meta.com/trust-and-safety/" rel="nofollow">safeguards</a> that developers should deploy with Llama models or other LLMs, including Llama Guard 3, Prompt Guard and Code Shield. All our <a href="https://github.com/meta-llama/llama-agentic-system" rel="nofollow">reference implementations</a> demos contain these safeguards by default so developers can benefit from system-level safety out-of-the-box. </p>1291<h4 class="relative group flex items-baseline">1292 <a id="new-capabilities" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#new-capabilities" rel="nofollow">1293 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>1294 </a>1295 <span>1296 New capabilities1297 </span>1298</h4>1299<p>Note that this release introduces new capabilities, including a longer context window, multilingual inputs and outputs and possible integrations by developers with third party tools. Building with these new capabilities requires specific considerations in addition to the best practices that generally apply across all Generative AI use cases.</p>1300<p><strong>Tool-use</strong>: Just like in standard software development, developers are responsible for the integration of the LLM with the tools and services of their choice. They should define a clear policy for their use case and assess the integrity of the third party services they use to be aware of the safety and security limitations when using this capability. Refer to the Responsible Use Guide for best practices on the safe deployment of the third party safeguards. </p>1301<p><strong>Multilinguality</strong>: Llama 3.1 supports 7 languages in addition to English: French, German, Hindi, Italian, Portuguese, Spanish, and Thai. Llama may be able to output text in other languages than those that meet performance thresholds for safety and helpfulness. We strongly discourage developers from using this model to converse in non-supported languages without implementing finetuning and system controls in alignment with their policies and the best practices shared in the Responsible Use Guide. </p>1302<h3 class="relative group flex items-baseline">1303 <a id="evaluations" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#evaluations" rel="nofollow">1304 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>1305 </a>1306 <span>1307 Evaluations1308 </span>1309</h3>1310<p>We evaluated Llama models for common use cases as well as specific capabilities. Common use cases evaluations measure safety risks of systems for most commonly built applications including chat bot, coding assistant, tool calls. We built dedicated, adversarial evaluation datasets and evaluated systems composed of Llama models and Llama Guard 3 to filter input prompt and output response. It is important to evaluate applications in context, and we recommend building dedicated evaluation dataset for your use case. Prompt Guard and Code Shield are also available if relevant to the application. </p>1311<p>Capability evaluations measure vulnerabilities of Llama models inherent to specific capabilities, for which were crafted dedicated benchmarks including long context, multilingual, tools calls, coding or memorization.</p>1312<p><strong>Red teaming</strong></p>1313<p>For both scenarios, we conducted recurring red teaming exercises with the goal of discovering risks via adversarial prompting and we used the learnings to improve our benchmarks and safety tuning datasets. </p>1314<p>We partnered early with subject-matter experts in critical risk areas to understand the nature of these real-world harms and how such models may lead to unintended harm for society. Based on these conversations, we derived a set of adversarial goals for the red team to attempt to achieve, such as extracting harmful information or reprogramming the model to act in a potentially harmful capacity. The red team consisted of experts in cybersecurity, adversarial machine learning, responsible AI, and integrity in addition to multilingual content specialists with background in integrity issues in specific geographic markets.</p>1315<h3 class="relative group flex items-baseline">1316 <a id="critical-and-other-risks" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#critical-and-other-risks" rel="nofollow">1317 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>1318 </a>1319 <span>1320 Critical and other risks1321 </span>1322</h3>1323<p>We specifically focused our efforts on mitigating the following critical risk areas:</p>1324<p><strong>1- CBRNE (Chemical, Biological, Radiological, Nuclear, and Explosive materials) helpfulness</strong></p>1325<p>To assess risks related to proliferation of chemical and biological weapons, we performed uplift testing designed to assess whether use of Llama 3.1 models could meaningfully increase the capabilities of malicious actors to plan or carry out attacks using these types of weapons. </p>1326<p><strong>2. Child Safety</strong></p>1327<p>Child Safety risk assessments were conducted using a team of experts, to assess the model’s capability to produce outputs that could result in Child Safety risks and inform on any necessary and appropriate risk mitigations via fine tuning. We leveraged those expert red teaming sessions to expand the coverage of our evaluation benchmarks through Llama 3 model development. For Llama 3, we conducted new in-depth sessions using objective based methodologies to assess the model risks along multiple attack vectors including the additional languages Llama 3 is trained on. We also partnered with content specialists to perform red teaming exercises assessing potentially violating content while taking account of market specific nuances or experiences. </p>1328<p><strong>3. Cyber attack enablement</strong></p>1329<p>Our cyber attack uplift study investigated whether LLMs can enhance human capabilities in hacking tasks, both in terms of skill level and speed.</p>1330<p>Our attack automation study focused on evaluating the capabilities of LLMs when used as autonomous agents in cyber offensive operations, specifically in the context of ransomware attacks. This evaluation was distinct from previous studies that considered LLMs as interactive assistants. The primary objective was to assess whether these models could effectively function as independent agents in executing complex cyber-attacks without human intervention.</p>1331<p>Our study of Llama-3.1-405B’s social engineering uplift for cyber attackers was conducted to assess the effectiveness of AI models in aiding cyber threat actors in spear phishing campaigns. Please read our Llama 3.1 Cyber security whitepaper to learn more.</p>1332<h3 class="relative group flex items-baseline">1333 <a id="community" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#community" rel="nofollow">1334 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>1335 </a>1336 <span>1337 Community1338 </span>1339</h3>1340<p>Generative AI safety requires expertise and tooling, and we believe in the strength of the open community to accelerate its progress. We are active members of open consortiums, including the AI Alliance, Partnership on AI and MLCommons, actively contributing to safety standardization and transparency. We encourage the community to adopt taxonomies like the MLCommons Proof of Concept evaluation to facilitate collaboration and transparency on safety and content evaluations. Our Purple Llama tools are open sourced for the community to use and widely distributed across ecosystem partners including cloud service providers. We encourage community contributions to our <a href="https://github.com/meta-llama/PurpleLlama" rel="nofollow">Github repository</a>. </p>1341<p>We also set up the <a href="https://llama.meta.com/llama-impact-grants/" rel="nofollow">Llama Impact Grants</a> program to identify and support the most compelling applications of Meta’s Llama model for societal benefit across three categories: education, climate and open innovation. The 20 finalists from the hundreds of applications can be found <a href="https://llama.meta.com/llama-impact-grants/#finalists" rel="nofollow">here</a>. </p>1342<p>Finally, we put in place a set of resources including an <a href="https://developers.facebook.com/llama_output_feedback" rel="nofollow">output reporting mechanism</a> and <a href="https://www.facebook.com/whitehat" rel="nofollow">bug bounty program</a> to continuously improve the Llama technology with the help of the community.</p>1343<h2 class="relative group flex items-baseline">1344 <a id="ethical-considerations-and-limitations" class="block pr-1.5 text-lg md:absolute md:p-1.5 md:opacity-0 md:group-hover:opacity-100 md:right-full" href="#ethical-considerations-and-limitations" rel="nofollow">1345 <span class="header-link"><svg class="text-gray-500 hover:text-black dark:hover:text-gray-200 w-4" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span>1346 </a>1347 <span>1348 Ethical Considerations and Limitations1349 </span>1350</h2>1351<p>The core values of Llama 3.1 are openness, inclusivity and helpfulness. It is meant to serve everyone, and to work for a wide range of use cases. It is thus designed to be accessible to people across many different backgrounds, experiences and perspectives. Llama 3.1 addresses users and their needs as they are, without insertion unnecessary judgment or normativity, while reflecting the understanding that even content that may appear problematic in some cases can serve valuable purposes in others. It respects the dignity and autonomy of all users, especially in terms of the values of free thought and expression that power innovation and progress. </p>1352<p>But Llama 3.1 is a new technology, and like any new technology, there are risks associated with its use. Testing conducted to date has not covered, nor could it cover, all scenarios. For these reasons, as with all LLMs, Llama 3.1’s potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts. Therefore, before deploying any applications of Llama 3.1 models, developers should perform safety testing and tuning tailored to their specific applications of the model. Please refer to available resources including our <a href="https://llama.meta.com/responsible-use-guide" rel="nofollow">Responsible Use Guide</a>, <a href="https://llama.meta.com/trust-and-safety/" rel="nofollow">Trust and Safety</a> solutions, and other <a href="https://llama.meta.com/docs/get-started/" rel="nofollow">resources</a> to learn more about responsible development. </p>1353<!----></div> <!--[-1--><!--]--><!----><!--]--></div><!--]--><!--]--><!----></section><!----> <section class="pt-8 border-gray-100 md:col-span-5 pt-6 md:pb-24 md:pl-6 md:border-l order-first md:order-none"><!--[-1--><div class="flex justify-between pb-2"><dl><dt class="-mb-1 text-sm text-gray-500">Downloads last month</dt> <dd class="font-semibold">5,620,096</dd> <!--[-1--><!--]--></dl> <div class="model-graph h-[40px] w-[200px] flex-none md:w-[150px] lg:w-[200px]"><!---->1354 <svg 1355 viewbox="0 0 100 100" 1356 width="100%" 1357 height="100%" 1358 preserveAspectRatio="none"1359 style="overflow: visible;"1360 >1361 <defs>1362 <linearGradient id="fill-gradient" x1="0%" y1="0%" x2="0%" y2="100%">1363 <stop offset="0%" style="stop-color: rgb(137, 86, 255); 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(if you are located outside of the EEA or Switzerland).\n \n1. License Rights and Redistribution.\na. Grant of Rights. You are granted a non-exclusive, worldwide, non-transferable and royalty-free limited license under Meta’s intellectual property or other rights owned by Meta embodied in the Llama Materials to use, reproduce, distribute, copy, create derivative works of, and make modifications to the Llama Materials.\nb. Redistribution and Use.\ni. If you distribute or make available the Llama Materials (or any derivative works thereof), or a product or service (including another AI model) that contains any of them, you shall (A) provide a copy of this Agreement with any such Llama Materials; and (B) prominently display “Built with Llama” on a related website, user interface, blogpost, about page, or product documentation. If you use the Llama Materials or any outputs or results of the Llama Materials to create, train, fine tune, or otherwise improve an AI model, which is distributed or made available, you shall also include “Llama” at the beginning of any such AI model name.\nii. If you receive Llama Materials, or any derivative works thereof, from a Licensee as part of an integrated end user product, then Section 2 of this Agreement will not apply to you.\niii. You must retain in all copies of the Llama Materials that you distribute the following attribution notice within a “Notice” text file distributed as a part of such copies: “Llama 3.1 is licensed under the Llama 3.1 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.”\niv. Your use of the Llama Materials must comply with applicable laws and regulations (including trade compliance laws and regulations) and adhere to the Acceptable Use Policy for the Llama Materials (available at https://llama.meta.com/llama3_1/use-policy), which is hereby incorporated by reference into this Agreement.\n2. Additional Commercial Terms. If, on the Llama 3.1 version release date, the monthly active users of the products or services made available by or for Licensee, or Licensee’s affiliates, is greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta, which Meta may grant to you in its sole discretion, and you are not authorized to exercise any of the rights under this Agreement unless or until Meta otherwise expressly grants you such rights.\n3. Disclaimer of Warranty. UNLESS REQUIRED BY APPLICABLE LAW, THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS THEREFROM ARE PROVIDED ON AN “AS IS” BASIS, WITHOUT WARRANTIES OF ANY KIND, AND META DISCLAIMS ALL WARRANTIES OF ANY KIND, BOTH EXPRESS AND IMPLIED, INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING OR REDISTRIBUTING THE LLAMA MATERIALS AND ASSUME ANY RISKS ASSOCIATED WITH YOUR USE OF THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS.\n4. Limitation of Liability. IN NO EVENT WILL META OR ITS AFFILIATES BE LIABLE UNDER ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, TORT, NEGLIGENCE, PRODUCTS LIABILITY, OR OTHERWISE, ARISING OUT OF THIS AGREEMENT, FOR ANY LOST PROFITS OR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL, EXEMPLARY OR PUNITIVE DAMAGES, EVEN IF META OR ITS AFFILIATES HAVE BEEN ADVISED OF THE POSSIBILITY OF ANY OF THE FOREGOING.\n5. Intellectual Property.\na. No trademark licenses are granted under this Agreement, and in connection with the Llama Materials, neither Meta nor Licensee may use any name or mark owned by or associated with the other or any of its affiliates, except as required for reasonable and customary use in describing and redistributing the Llama Materials or as set forth in this Section 5(a). Meta hereby grants you a license to use “Llama” (the “Mark”) solely as required to comply with the last sentence of Section 1.b.i. You will comply with Meta’s brand guidelines (currently accessible at https://about.meta.com/brand/resources/meta/company-brand/ ). All goodwill arising out of your use of the Mark will inure to the benefit of Meta.\nb. Subject to Meta’s ownership of Llama Materials and derivatives made by or for Meta, with respect to any derivative works and modifications of the Llama Materials that are made by you, as between you and Meta, you are and will be the owner of such derivative works and modifications.\nc. If you institute litigation or other proceedings against Meta or any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Llama Materials or Llama 3.1 outputs or results, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by you, then any licenses granted to you under this Agreement shall terminate as of the date such litigation or claim is filed or instituted. You will indemnify and hold harmless Meta from and against any claim by any third party arising out of or related to your use or distribution of the Llama Materials.\n6. Term and Termination. The term of this Agreement will commence upon your acceptance of this Agreement or access to the Llama Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein. Meta may terminate this Agreement if you are in breach of any term or condition of this Agreement. Upon termination of this Agreement, you shall delete and cease use of the Llama Materials. Sections 3, 4 and 7 shall survive the termination of this Agreement.\n7. Governing Law and Jurisdiction. This Agreement will be governed and construed under the laws of the State of California without regard to choice of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement. The courts of California shall have exclusive jurisdiction of any dispute arising out of this Agreement.\n### Llama 3.1 Acceptable Use Policy\nMeta is committed to promoting safe and fair use of its tools and features, including Llama 3.1. If you access or use Llama 3.1, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of this policy can be found at [https://llama.meta.com/llama3_1/use-policy](https://llama.meta.com/llama3_1/use-policy)\n#### Prohibited Uses\nWe want everyone to use Llama 3.1 safely and responsibly. You agree you will not use, or allow others to use, Llama 3.1 to:\n 1. Violate the law or others’ rights, including to:\n 1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:\n 1. Violence or terrorism\n 2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material\n 3. Human trafficking, exploitation, and sexual violence\n 4. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.\n 5. Sexual solicitation\n 6. Any other criminal activity\n 3. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals\n 4. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services\n 5. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices\n 6. Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws\n 7. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama Materials\n 8. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system\n2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama 3.1 related to the following:\n 1. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State\n 2. Guns and illegal weapons (including weapon development)\n 3. Illegal drugs and regulated/controlled substances\n 4. Operation of critical infrastructure, transportation technologies, or heavy machinery\n 5. Self-harm or harm to others, including suicide, cutting, and eating disorders\n 6. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual\n3. Intentionally deceive or mislead others, including use of Llama 3.1 related to the following:\n 1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation\n 2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content\n 3. Generating, promoting, or further distributing spam\n 4. Impersonating another individual without consent, authorization, or legal right\n 5. Representing that the use of Llama 3.1 or outputs are human-generated\n 6. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement\n4. Fail to appropriately disclose to end users any known dangers of your AI system\nPlease report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means:\n * Reporting issues with the model: [https://github.com/meta-llama/llama-models/issues](https://github.com/meta-llama/llama-models/issues)\n * Reporting risky content generated by the model:\n developers.facebook.com/llama_output_feedback\n * Reporting bugs and security concerns: facebook.com/whitehat/info\n * Reporting violations of the Acceptable Use Policy or unlicensed uses of Meta Llama 3: LlamaUseReport@meta.com","extra_gated_fields":{"First Name":"text","Last Name":"text","Date of birth":"date_picker","Country":"country","Affiliation":"text","Job title":{"type":"select","options":["Student","Research Graduate","AI researcher","AI developer/engineer","Reporter","Other"]},"geo":"ip_location","By clicking Submit below I accept the terms of the license and acknowledge that the information I provide will be collected stored processed and shared in accordance with the Meta Privacy Policy":"checkbox"},"extra_gated_description":"The information you provide will be collected, stored, processed and shared in accordance with the [Meta Privacy Policy](https://www.facebook.com/privacy/policy/).","extra_gated_button_content":"Submit"},"cardExists":true,"config":{"architectures":["LlamaForCausalLM"],"model_type":"llama","tokenizer_config":{"bos_token":"<|begin_of_text|>","chat_template":"{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. 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specifications, manuals and documentation accompanying Llama 3.1 distributed by Meta at https://llama.meta.com/doc/overview.\n\"Licensee\" or \"you\" means you, or your employer or any other person or entity (if you are entering into this Agreement on such person or entity’s behalf), of the age required under applicable laws, rules or regulations to provide legal consent and that has legal authority to bind your employer or such other person or entity if you are entering in this Agreement on their behalf.\n\"Llama 3.1\" means the foundational large language models and software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Meta at https://llama.meta.com/llama-downloads.\n\"Llama Materials\" means, collectively, Meta’s proprietary Llama 3.1 and Documentation (and any portion thereof) made available under this Agreement.\n\"Meta\" or \"we\" means Meta Platforms Ireland Limited (if you are located in or, if you are an entity, your principal place of business is in the EEA or Switzerland) and Meta Platforms, Inc. (if you are located outside of the EEA or Switzerland).\n \n1. License Rights and Redistribution.\na. Grant of Rights. You are granted a non-exclusive, worldwide, non-transferable and royalty-free limited license under Meta’s intellectual property or other rights owned by Meta embodied in the Llama Materials to use, reproduce, distribute, copy, create derivative works of, and make modifications to the Llama Materials.\nb. Redistribution and Use.\ni. If you distribute or make available the Llama Materials (or any derivative works thereof), or a product or service (including another AI model) that contains any of them, you shall (A) provide a copy of this Agreement with any such Llama Materials; and (B) prominently display “Built with Llama” on a related website, user interface, blogpost, about page, or product documentation. 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Your use of the Llama Materials must comply with applicable laws and regulations (including trade compliance laws and regulations) and adhere to the Acceptable Use Policy for the Llama Materials (available at https://llama.meta.com/llama3_1/use-policy), which is hereby incorporated by reference into this Agreement.\n2. Additional Commercial Terms. If, on the Llama 3.1 version release date, the monthly active users of the products or services made available by or for Licensee, or Licensee’s affiliates, is greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta, which Meta may grant to you in its sole discretion, and you are not authorized to exercise any of the rights under this Agreement unless or until Meta otherwise expressly grants you such rights.\n3. Disclaimer of Warranty. UNLESS REQUIRED BY APPLICABLE LAW, THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS THEREFROM ARE PROVIDED ON AN “AS IS” BASIS, WITHOUT WARRANTIES OF ANY KIND, AND META DISCLAIMS ALL WARRANTIES OF ANY KIND, BOTH EXPRESS AND IMPLIED, INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING OR REDISTRIBUTING THE LLAMA MATERIALS AND ASSUME ANY RISKS ASSOCIATED WITH YOUR USE OF THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS.\n4. Limitation of Liability. IN NO EVENT WILL META OR ITS AFFILIATES BE LIABLE UNDER ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, TORT, NEGLIGENCE, PRODUCTS LIABILITY, OR OTHERWISE, ARISING OUT OF THIS AGREEMENT, FOR ANY LOST PROFITS OR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL, EXEMPLARY OR PUNITIVE DAMAGES, EVEN IF META OR ITS AFFILIATES HAVE BEEN ADVISED OF THE POSSIBILITY OF ANY OF THE FOREGOING.\n5. 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Subject to Meta’s ownership of Llama Materials and derivatives made by or for Meta, with respect to any derivative works and modifications of the Llama Materials that are made by you, as between you and Meta, you are and will be the owner of such derivative works and modifications.\nc. If you institute litigation or other proceedings against Meta or any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Llama Materials or Llama 3.1 outputs or results, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by you, then any licenses granted to you under this Agreement shall terminate as of the date such litigation or claim is filed or instituted. You will indemnify and hold harmless Meta from and against any claim by any third party arising out of or related to your use or distribution of the Llama Materials.\n6. Term and Termination. The term of this Agreement will commence upon your acceptance of this Agreement or access to the Llama Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein. Meta may terminate this Agreement if you are in breach of any term or condition of this Agreement. Upon termination of this Agreement, you shall delete and cease use of the Llama Materials. Sections 3, 4 and 7 shall survive the termination of this Agreement.\n7. Governing Law and Jurisdiction. This Agreement will be governed and construed under the laws of the State of California without regard to choice of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement. The courts of California shall have exclusive jurisdiction of any dispute arising out of this Agreement.\n### Llama 3.1 Acceptable Use Policy\nMeta is committed to promoting safe and fair use of its tools and features, including Llama 3.1. If you access or use Llama 3.1, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of this policy can be found at [https://llama.meta.com/llama3_1/use-policy](https://llama.meta.com/llama3_1/use-policy)\n#### Prohibited Uses\nWe want everyone to use Llama 3.1 safely and responsibly. You agree you will not use, or allow others to use, Llama 3.1 to:\n 1. Violate the law or others’ rights, including to:\n 1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:\n 1. Violence or terrorism\n 2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material\n 3. Human trafficking, exploitation, and sexual violence\n 4. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.\n 5. Sexual solicitation\n 6. Any other criminal activity\n 3. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals\n 4. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services\n 5. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices\n 6. Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws\n 7. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama Materials\n 8. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system\n2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama 3.1 related to the following:\n 1. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State\n 2. Guns and illegal weapons (including weapon development)\n 3. 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14.0067 17.7582 14.1006 17.6173 14.1487L16.4782 14.5364C16.4113 14.5592 16.3399 14.5709 16.2678 14.5709H16.2663ZM16.2663 18.9993C16.1334 18.9995 16.0046 18.9601 15.902 18.8878C15.7995 18.8156 15.7297 18.715 15.7046 18.6035C15.6795 18.4919 15.7007 18.3764 15.7645 18.2768C15.8283 18.1772 15.9308 18.0997 16.0543 18.0577L17.1934 17.67C17.2638 17.6429 17.3398 17.6283 17.417 17.627C17.4942 17.6257 17.5709 17.6378 17.6425 17.6625C17.714 17.6873 17.779 17.7241 17.8335 17.7709C17.8879 17.8176 17.9307 17.8734 17.9593 17.9346C17.9879 17.9959 18.0017 18.0615 17.9998 18.1275C17.998 18.1935 17.9805 18.2584 17.9484 18.3184C17.9164 18.3785 17.8705 18.4323 17.8134 18.4768C17.7564 18.5212 17.6894 18.5554 17.6165 18.5771L16.4775 18.9648C16.4103 18.9878 16.3386 18.9995 16.2663 18.9993Z" fill="#5699DB"></path></svg><!--]--></li><!--]--> <!--[0--><li class="select-none text-sm text-gray-500">+1</li><!--]--></ul><!--]--></div><!----><!--]--> <!--[-1--><!--]--></button> <!--[-1--><!--]--> <!--[-1--><!--]--></div><!--]--></div></div><!--]--><!----> <div class="flex w-full max-w-full flex-wrap items-center"><!--[0--><div class="flex items-center gap-4 text-sm text-gray-500"><a href="/tasks/text-generation" target="_blank" title="Learn more about text-generation"><div class="inline-flex items-center hover:underline"><!--[--><svg class="mr-1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 18 18"><path d="M16.2607 8.08202L14.468 6.28928C14.3063 6.12804 14.0873 6.03749 13.859 6.03749C13.6307 6.03749 13.4117 6.12804 13.25 6.28928L5.6375 13.904V16.9125H8.64607L16.2607 9.30002C16.422 9.13836 16.5125 8.91935 16.5125 8.69102C16.5125 8.4627 16.422 8.24369 16.2607 8.08202V8.08202ZM8.1953 15.825H6.725V14.3547L11.858 9.22118L13.3288 10.6915L8.1953 15.825ZM14.0982 9.92262L12.6279 8.45232L13.8606 7.21964L15.3309 8.68994L14.0982 9.92262Z"></path><path d="M6.18125 9.84373H7.26875V6.03748H8.9V4.94998H4.55V6.03748H6.18125V9.84373Z"></path><path d="M4.55 11.475H2.375V2.775H11.075V4.95H12.1625V2.775C12.1625 2.48658 12.0479 2.20997 11.844 2.00602C11.64 1.80208 11.3634 1.6875 11.075 1.6875H2.375C2.08658 1.6875 1.80997 1.80208 1.60602 2.00602C1.40207 2.20997 1.2875 2.48658 1.2875 2.775V11.475C1.2875 11.7634 1.40207 12.04 1.60602 12.244C1.80997 12.4479 2.08658 12.5625 2.375 12.5625H4.55V11.475Z"></path></svg><!--]--><!----> <span>Text Generation</span></div></a></div><!--]--><!----> <div class="ml-auto flex gap-3"><!--[-1--><!--]--> <!--[0--><div class="flex gap-x-1 peer:"><!--[-1--><!--]--> <div class="relative "><!--[-1--><span class="inline-block w-full"><span class="contents"><div class="inline-flex w-32 cursor-pointer justify-between rounded-md border border-gray-100 px-4 py-1 hover:text-gray-700 dark:hover:text-gray-200"><div class="truncate text-sm">Examples</div> <svg class="-mr-1 ml-2 h-5 w-5 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class="flex flex-wrap items-center gap-x-2"><button class="flex items-center hover:text-gray-700 dark:hover:text-gray-300" type="button"><svg class="mr-1 shrink-0" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" style="transform: rotate(360deg);"><path d="M31 16l-7 7l-1.41-1.41L28.17 16l-5.58-5.59L24 9l7 7z" fill="currentColor"></path><path d="M1 16l7-7l1.41 1.41L3.83 16l5.58 5.59L8 23l-7-7z" fill="currentColor"></path><path d="M12.419 25.484L17.639 6l1.932.518L14.35 26z" fill="currentColor"></path></svg><!----> <div class="text-nowrap">View Code <span class="max-xl:hidden">Snippets</span></div></button> <!--[-1--><!--]--></div><!----></span> <!--[-1--><!--]--></span><!--]--> <!--[-1--><!--]--> <!--[-1--><!--]--></div> <div class="flex flex-wrap items-center justify-end gap-x-2"><!--[0--><a href="/inference/models?model=meta-llama%2FLlama-3.1-8B-Instruct" class="flex items-center whitespace-nowrap hover:text-gray-700 dark:hover:text-gray-300"><svg class="mr-1 shrink-0" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 9 7"><path fill="currentColor" d="M8.537 1.153H7.361A1.445 1.445 0 0 0 5.954 0c-.689 0-1.263.49-1.407 1.153H.5v.576h4.047a1.445 1.445 0 0 0 1.407 1.153c.689 0 1.263-.49 1.407-1.153h1.176v-.576M5.954 2.305a.847.847 0 0 1-.861-.864c0-.49.373-.865.861-.865s.861.375.861.865-.373.864-.861.864M.5 5.764h1.177a1.445 1.445 0 0 0 1.406 1.152c.69 0 1.263-.49 1.407-1.152h4.047v-.577H4.49a1.445 1.445 0 0 0-1.407-1.152c-.688 0-1.263.49-1.406 1.152H.5v.577M3.083 4.61c.488 0 .862.375.862.864 0 .49-.374.865-.862.865a.847.847 0 0 1-.86-.865c0-.49.372-.864.86-.864"></path></svg><!----> Compare providers</a><!--]--></div></div> <!--[-1--><!--]--><!----><!--]--> <!--[-1--><!--]--> <!--[-1--><!--]--></form> <!--[-1--><!--]--> <dialog class="shadow-alternate z-40 mx-4 my-auto h-fit select-text overflow-hidden rounded-xl bg-white max-sm:max-w-[calc(100dvw-2rem)] sm:mx-auto lg:mt-26 md:portrait:mt-30 xl:mt-30 2xl:mt-32 w-full lg:w-10/12 xl:w-8/12 2xl:w-7/12 max-w-[calc(100%-4rem)] lg:max-w-4xl "><div tabindex="-1" class="outline-none focus:ring-0 focus-visible:ring-0"><!--[-1--><!--]--></div></dialog><!----><!--]--><!----></div></div><!--]--> <!--[0--><div class="divider-column-vertical"></div> <h2 class="text-smd mb-3 flex items-baseline overflow-hidden whitespace-nowrap font-semibold text-gray-800"><svg class="mr-1 inline self-center flex-none" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 16 16"><path fill-rule="evenodd" clip-rule="evenodd" d="M3.9 5.34v4.07a3.68 3.68 0 0 0 3.68 3.68h1.99v-1.47H7.58c-1.21 0-2.2-1-2.2-2.21v-1.6c.63.5 1.4.76 2.2.76h1.99V7.1H7.58a2.21 2.21 0 0 1-2.16-1.76H3.9Z" fill="currentColor" fill-opacity=".5"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M2.9 2.36c0-.3.25-.55.55-.55h2.43c.3 0 .55.25.55.55v2.43c0 .3-.24.55-.55.55H3.45a.55.55 0 0 1-.55-.55V2.36Zm6.67 4.23c0-.3.24-.55.55-.55h2.43c.3 0 .55.25.55.55v2.44c0 .3-.25.55-.55.55h-2.43a.55.55 0 0 1-.55-.55V6.59Zm.55 4.07c-.3 0-.55.24-.55.55v2.43c0 .3.24.55.55.55h2.43c.3 0 .55-.25.55-.55v-2.43c0-.3-.25-.55-.55-.55h-2.43Z" fill="currentColor" fill-opacity=".85"></path></svg><!----> Model tree for <span class="ml-1 truncate font-mono text-[0.86rem] font-medium">meta-llama/Llama-3.1-8B-Instruct</span> <a href="/docs/hub/model-cards#specifying-a-base-model" target="_blank" class="ml-1 translate-y-px self-center text-xs text-gray-400 hover:text-gray-700 dark:hover:text-gray-200 max-xl:hidden"><svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M17 22v-8h-4v2h2v6h-3v2h8v-2h-3z" fill="currentColor"></path><path d="M16 8a1.5 1.5 0 1 0 1.5 1.5A1.5 1.5 0 0 0 16 8z" fill="currentColor"></path><path d="M16 30a14 14 0 1 1 14-14a14 14 0 0 1-14 14zm0-26a12 12 0 1 0 12 12A12 12 0 0 0 16 4z" fill="currentColor"></path></svg><!----></a></h2> <div class="text-smd flex flex-col space-y-0 whitespace-nowrap pl-1 text-gray-800"><!--[-1--><!--[0--><!--[--><!--[0--><!--[2--><div class="flex h-[28px] w-full items-center justify-between gap-1.5"><p class="font-semibold">Base model</p> <div class="flex-1 translate-y-[2.5px] self-center border-b border-dotted dark:border-gray-800"></div> <a href="/meta-llama/Llama-3.1-8B" class="truncate font-mono text-xs underline decoration-gray-300 hover:decoration-gray-600 dark:decoration-gray-500 dark:hover:decoration-gray-200">meta-llama/Llama-3.1-8B</a></div><!--]--><!--]--><!--[-1--><div class="flex h-[28px] items-center justify-between gap-1.5" style="padding-left: 0px;"><div class="relative h-[28px] w-[19px] flex-none"><svg class="text-gray-300 dark:text-gray-700" width="15" height="28" viewBox="0 0 15 28" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M0.967742 0C0.967742 7.67991 7.21819 13.9655 15 13.9655V15C6.74768 15 0 8.3173 0 0H0.967742Z" fill="currentColor"></path></svg><!----></div> <!--[0--><!--[-1--><div class="mr-auto flex items-center font-semibold"><!--[2--><svg class="mr-1 inline self-center flex-none text-gray-400" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 17 17"><path opacity="0.25" d="M12.1072 5.27442L7.39274 8.00113L2.67828 5.27442C2.77506 5.10687 2.9131 4.96686 3.07927 4.86771L6.8199 2.70811C7.17506 2.50762 7.61042 2.50762 7.96558 2.70811L11.7062 4.86771C11.8723 4.96681 12.0104 5.10715 12.1072 5.27442Z" fill="currentColor"></path><path opacity="0.5" d="M7.3928 8.00112V13.4431C7.21219 13.4428 7.03398 13.4017 6.87152 13.3228L3.09652 11.1403C2.92264 11.0397 2.77822 10.8952 2.6777 10.7213C2.57717 10.5474 2.52406 10.3501 2.52368 10.1493V5.85298C2.52463 5.65003 2.5779 5.45076 2.67835 5.27441L7.3928 8.00112Z" fill="currentColor"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M12.2621 7.17681V5.85298C12.261 5.6502 12.2077 5.45085 12.1075 5.27441L7.39301 8.00112V13.4431C7.56715 13.4419 7.73957 13.403 7.8971 13.3285L9.44011 12.4381C9.39138 12.3915 9.34927 12.338 9.31521 12.2791C9.25238 12.1704 9.21919 12.0471 9.21895 11.9215V9.23635C9.21955 9.10957 9.25281 8.98509 9.31553 8.87491L9.31524 8.87474C9.37573 8.77002 9.462 8.68251 9.56586 8.62054L11.9037 7.27079C12.0148 7.20808 12.1385 7.17675 12.2621 7.17681Z" fill="currentColor"></path><path opacity="0.25" d="M15.2083 8.87475L12.2617 10.5789L9.31519 8.87475C9.37567 8.77002 9.46195 8.68252 9.5658 8.62055L11.9037 7.2708C12.1257 7.14549 12.3978 7.14549 12.6197 7.2708L14.9576 8.62055C15.0615 8.68249 15.1477 8.7702 15.2083 8.87475Z" fill="currentColor"></path><path opacity="0.5" d="M12.2621 10.5789V13.9801C12.1492 13.9799 12.0378 13.9542 11.9363 13.9049L9.5769 12.5409C9.46822 12.478 9.37796 12.3877 9.31513 12.279C9.2523 12.1703 9.21911 12.047 9.21887 11.9215V9.2363C9.21946 9.10946 9.25276 8.98491 9.31554 8.87469L12.2621 10.5789Z" fill="currentColor"></path><path d="M15.3052 9.2363V11.9215C15.305 12.047 15.2718 12.1703 15.209 12.279C15.1461 12.3877 15.0559 12.478 14.9472 12.5409L12.5771 13.9085C12.4786 13.9551 12.3709 13.9794 12.262 13.9801V10.5789L15.2086 8.87469C15.2712 8.98497 15.3045 9.10956 15.3052 9.2363Z" fill="currentColor"></path></svg><!----> Finetuned<!--]--></div><!--]--> <!--[0--><span class="-ml-0.5 text-gray-600 dark:text-gray-400">(<a href="/models?other=base_model:finetune:meta-llama/Llama-3.1-8B" class="underline decoration-gray-300 hover:text-gray-900 hover:decoration-gray-600 dark:text-gray-300 dark:decoration-gray-500 dark:hover:text-gray-100 dark:hover:decoration-gray-200">1477</a>)</span><!--]--> <div class="flex-1 translate-y-[2.5px] self-center border-b border-dotted dark:border-gray-800"></div><!--]--> <!--[0--><div class="flex items-center justify-center rounded-full bg-blue-500/10 px-2 text-blue-600 dark:text-blue-500" title="meta-llama/Llama-3.1-8B-Instruct">this model</div><!--]--><!----></div><!--]--><!--]--><!--]--> <!--[0--><div class="flex w-full flex-col justify-center space-y-0" style="padding-left: 24px;"><!--[--><!--[0--><div class="@container flex h-[28px] w-full items-center justify-between gap-1.5"><div class="relative h-[28px] w-[19px] flex-none"><div class="left absolute inset-y-0 -top-[3px] left-0 w-px bg-gray-300 dark:bg-gray-700"></div> <svg class="text-gray-300 dark:text-gray-700" width="19" height="28" viewBox="0 0 19 28" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M1 0C1 7.42391 7.4588 13.5 15.5 13.5V14.5C6.9726 14.5 0 8.04006 0 0H1Z" fill="currentColor"></path></svg></div> <div class="font-semibold"><!--[0-->Adapters<!--]--></div> <div class="flex-1 translate-y-[2.5px] self-center border-b border-dotted dark:border-gray-800"></div> <!--[-1--><!--]--> <a class="text-gray-700 underline decoration-gray-300 hover:text-gray-900 hover:decoration-gray-600 dark:text-gray-300 dark:decoration-gray-500 dark:hover:text-gray-100 dark:hover:decoration-gray-200" href="/models?other=base_model:adapter:meta-llama/Llama-3.1-8B-Instruct">2886 models</a></div><!--]--><!--[0--><div class="@container flex h-[28px] w-full items-center justify-between gap-1.5"><div class="relative h-[28px] w-[19px] flex-none"><div class="left absolute inset-y-0 -top-[3px] left-0 w-px bg-gray-300 dark:bg-gray-700"></div> <svg class="text-gray-300 dark:text-gray-700" width="19" height="28" viewBox="0 0 19 28" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M1 0C1 7.42391 7.4588 13.5 15.5 13.5V14.5C6.9726 14.5 0 8.04006 0 0H1Z" fill="currentColor"></path></svg></div> <div class="font-semibold"><!--[3-->Finetunes<!--]--></div> <div class="flex-1 translate-y-[2.5px] self-center border-b border-dotted dark:border-gray-800"></div> <!--[-1--><!--]--> <a class="text-gray-700 underline decoration-gray-300 hover:text-gray-900 hover:decoration-gray-600 dark:text-gray-300 dark:decoration-gray-500 dark:hover:text-gray-100 dark:hover:decoration-gray-200" href="/models?other=base_model:finetune:meta-llama/Llama-3.1-8B-Instruct">3185 models</a></div><!--]--><!--[0--><div class="@container flex h-[28px] w-full items-center justify-between gap-1.5"><div class="relative h-[28px] w-[19px] flex-none"><div class="left absolute inset-y-0 -top-[3px] left-0 w-px bg-gray-300 dark:bg-gray-700"></div> <svg class="text-gray-300 dark:text-gray-700" width="19" height="28" viewBox="0 0 19 28" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M1 0C1 7.42391 7.4588 13.5 15.5 13.5V14.5C6.9726 14.5 0 8.04006 0 0H1Z" fill="currentColor"></path></svg></div> <div class="font-semibold"><!--[1-->Merges<!--]--></div> <div class="flex-1 translate-y-[2.5px] self-center border-b border-dotted dark:border-gray-800"></div> <!--[-1--><!--]--> <a class="text-gray-700 underline decoration-gray-300 hover:text-gray-900 hover:decoration-gray-600 dark:text-gray-300 dark:decoration-gray-500 dark:hover:text-gray-100 dark:hover:decoration-gray-200" href="/models?other=base_model:merge:meta-llama/Llama-3.1-8B-Instruct">103 models</a></div><!--]--><!--[0--><div class="@container flex h-[28px] w-full items-center justify-between gap-1.5"><div class="relative h-[28px] w-[19px] flex-none"><div class="left absolute inset-y-0 -top-[3px] left-0 bottom-[28px] w-px bg-gray-300 dark:bg-gray-700"></div> <svg class="text-gray-300 dark:text-gray-700" width="19" height="28" viewBox="0 0 19 28" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M1 0C1 7.42391 7.4588 13.5 15.5 13.5V14.5C6.9726 14.5 0 8.04006 0 0H1Z" fill="currentColor"></path></svg></div> <div class="font-semibold"><!--[2-->Quantizations<!--]--></div> <div class="flex-1 translate-y-[2.5px] self-center border-b border-dotted dark:border-gray-800"></div> <!--[0--><div class="gap-0.75 flex items-center"><!--[--><a href="/models?apps=llama.cpp&other=base_model:quantized:meta-llama/Llama-3.1-8B-Instruct" title="Use with llama.cpp" class="@max-[280px]:last:hidden"><!--[0--><!--[--><svg class="text-black size-3 " xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 12 12"><path fill="currentColor" d="M9.11 9.94c-.26.4-.7.64-1.18.64H3.25l1.83-3.17h5.5zM5.08 7.4H1.42l3.05-5.28c.25-.43.71-.7 1.21-.7h2.86z"></path></svg><!--]--><!--]--><!----></a><a href="/models?apps=lmstudio&other=base_model:quantized:meta-llama/Llama-3.1-8B-Instruct" title="Use with LM Studio" class="@max-[280px]:last:hidden"><!--[0--><!--[--><svg class="text-black size-3 " xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path fill="url(#icon-lm-studio-a)" d="M19.337 0H4.663A4.663 4.663 0 0 0 0 4.663v14.674A4.663 4.663 0 0 0 4.663 24h14.674A4.663 4.663 0 0 0 24 19.337V4.663A4.663 4.663 0 0 0 19.337 0"></path><g fill="#fff" opacity=".266"><path d="M15.803 4.35H7.418a1 1 0 0 0 0 2h8.385a1 1 0 0 0 0-2M19.928 7.063h-8.385a1 1 0 0 0 0 2h8.385a1 1 0 0 0 0-2M17.51 9.776H9.125a1 1 0 0 0 0 2h8.385a1 1 0 0 0 0-2M14.523 12.632H6.138a1 1 0 0 0 0 2h8.385a1 1 0 0 0 0-2M17.51 15.345H9.125a1 1 0 1 0 0 2h8.385a1 1 0 1 0 0-2M20.497 18.059h-4.829a1 1 0 1 0 0 1.999h4.829a1 1 0 1 0 0-2"></path></g><g fill="#fff" opacity=".845"><path d="M12.65 4.345H4.265a1 1 0 0 0 0 2h8.385a1 1 0 0 0 0-2M16.775 7.058H8.39a1 1 0 0 0 0 2h8.385a1 1 0 0 0 0-2M14.357 9.771H5.972a1 1 0 0 0 0 2h8.385a1 1 0 0 0 0-2M11.37 12.627H2.985a1 1 0 1 0 0 2h8.385a1 1 0 0 0 0-2M14.357 15.34H5.972a1 1 0 1 0 0 2h8.385a1 1 0 0 0 0-2M17.344 18.054h-4.828a1 1 0 1 0 0 1.999h4.828a1 1 0 1 0 0-2"></path></g><defs><linearGradient id="icon-lm-studio-a" x1="78.731" x2="2229.6" y1="0" y2="2218.01" gradientUnits="userSpaceOnUse"><stop stop-color="#6E7EF3"></stop><stop offset="1" stop-color="#4F13BE"></stop></linearGradient></defs></svg><!--]--><!--]--><!----></a><a href="/models?apps=jan&other=base_model:quantized:meta-llama/Llama-3.1-8B-Instruct" title="Use with Jan" class="@max-[280px]:last:hidden"><!--[0--><!--[--><svg class="text-black size-3 " xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 24 24"><path fill="#FFCA28" d="M3.197 11.75c-.53-.76-.742-1.477-.224-1.91.438-.369 1.082-.439 1.879.48 0 0 2.379 2.765 3.198 3.533.186.172.417.199.628-.02.178-.185.113-.346-.038-.568 0 0-3.354-4.986-3.794-5.595-.734-1.018-.451-1.676-.112-1.988.472-.438 1.303-.526 2.074.532l4.061 5.436a.36.36 0 0 0 .469.047l.056-.04a.357.357 0 0 0 .103-.468c-.711-1.238-3.54-6.171-3.955-7.07-.478-1.037-.273-1.564.233-1.869.601-.362 1.166-.336 1.841.667.732 1.092 3.574 5.69 4.296 6.926a.358.358 0 0 0 .464.14l.008-.004c.16-.077.303-.235.237-.458-.394-1.3-2.33-5.35-2.736-6.281-.555-1.272-.284-1.705.29-1.997.603-.305 1.23-.064 1.657.785.289.577 5.349 9.785 5.349 9.785-.074-1.373.273-2.345.568-3.322.539-1.776 1.841-2.7 2.785-2.284.491.216.58.646.527.976-.106.64-.557 2.626-.644 4.18-.205 3.644.897 7.843-3.208 10.483-2.747 1.767-5.691 1.456-7.636.096-2.359-1.647-7.944-9.57-8.376-10.192Z"></path><path fill="#EDA600" d="M22.176 9.682c-.343 1.442-.388 3.213-.377 3.968.045 2.94.03 5.484-2.918 7.809-.362.286-1.498.984-2.819 1.348-.425.115-.264.252-.002.222 1.443-.167 2.537-.79 3.145-1.181 4.103-2.64 3.094-6.81 3.3-10.454.086-1.555.56-4 .553-4.211-.01-.21-.539 1.056-.882 2.499M14.564 9.833s-.294.002-.572-.386c-.836-1.162-3.458-5.551-4.213-6.628-.86-1.229-1.663-.759-1.845-.66 0 0 .66.023 1.024.563.743 1.102 3.56 6.038 4.45 7.098.574.685 1.156.013 1.156.013M4.171 10.207c.258.277 2.522 2.963 3.356 3.712.716.643 1.251-.176 1.251-.176s-.263.036-.624-.235c-.894-.677-3.014-3.09-3.492-3.599-.709-.754-1.369-.282-1.509-.197.002 0 .408-.157 1.018.495M11.542 11.48s-.242.177-.688-.344c-.324-.381-4.046-4.922-4.046-4.922-.933-1.14-1.666-.8-1.818-.713 0 0 .468-.024 1.016.607.25.288 4.222 5.352 4.382 5.525.582.635 1.12.089 1.154-.152"></path><path fill="#EDA600" d="M19.165 10.83S14.235 2.564 13.92 2c-.7-1.25-1.513-.867-1.652-.804 0 0 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xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><rect x="2" y="2.49902" width="8" height="3.76425" rx="1.16774" fill="currentColor" fill-opacity="0.4"></rect><rect x="6.21875" y="6.7334" width="3.78055" height="3.76425" rx="1.16774" fill="currentColor" fill-opacity="0.7"></rect><rect x="2" y="6.73438" width="3.78055" height="3.76425" rx="1.16774" fill="currentColor" fill-opacity="0.5"></rect></svg><!----> Collection</div></header> <div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400"><!--[0--><span class="max-w-64 truncate">This collection hosts the transformers and original repos of the Llama 3.1, Llama Guard 3 and Prompt Guard models</span> <span class="px-1.5 text-gray-300">•</span><!--]--> <span>11 items</span> <span class="px-1.5 text-gray-300">•</span> <span class="truncate">Updated <time datetime="2024-12-06T16:49:01" title="2024-12-06T16:49:01.615Z">Dec 6, 2024</time></span> <!--[0--><span class="px-1.5 text-gray-300">•</span> <!--[-1--><svg class="flex-none w-3 mr-1 text-gray-400" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 12 12" fill="transparent"><path d="M9.30013 9.29152H9.3H2.7H2.69987C2.62308 9.29154 2.54762 9.27146 2.481 9.23328C2.41437 9.1951 2.3589 9.14015 2.32009 9.07389C2.28128 9.00763 2.26048 8.93237 2.25977 8.85558C2.25907 8.7798 2.27796 8.70513 2.31458 8.63882L5.62238 2.9426L5.67518 2.85168C5.7059 2.81806 5.74178 2.78928 5.78164 2.76649C5.84813 2.72848 5.9234 2.70848 6 2.70848C6.0766 2.70848 6.15187 2.72848 6.21836 2.76649C6.28441 2.80425 6.33953 2.85848 6.37836 2.92389L9.68527 8.63855C9.72199 8.70493 9.74093 8.7797 9.74023 8.85558C9.73952 8.93237 9.71872 9.00763 9.67991 9.07389C9.6411 9.14015 9.58563 9.1951 9.519 9.23328C9.45238 9.27146 9.37692 9.29154 9.30013 9.29152Z" stroke="currentColor"></path></svg><!--]--> 717<!--]--></div></a></article> <!--[0--><div class="overview-card-wrapper rounded-md! bg-linear-to-t! -z-1 from-gray-50! to-gray-50! shadow-none! dark:from-gray-925! dark:to-gray-925! -mt-[1.60rem] h-8 scale-x-[98%] transition-transform peer-hover:-translate-y-[2px] peer-hover:from-gray-100/80 dark:peer-hover:from-black"></div><!--]--></div><div class="flex flex-col"><article class="overview-card-wrapper group/collection rounded-md! from-white! to-white! dark:from-gray-900! dark:to-gray-900! relative peer"><a href="/collections/meta-llama/metas-llama-31-models-and-evals" class="block p-2"><header class="mb-0.5 flex items-center" title="Meta's Llama 3.1 models & evals"><h4 class="text-md text-smd truncate font-semibold group-hover/collection:underline">Meta's Llama 3.1 models & evals</h4> <div class="ml-2 flex items-center rounded-sm sm:ml-2.5 bg-orange-500/10 py-0.5 pl-1 pr-1.5 text-xs leading-none text-gray-700"><svg class="mr-0.5 flex-none text-orange-700" width="1em" height="1em" aria-hidden="true" focusable="false" role="img" viewBox="0 0 12 13" fill="none" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><rect x="2" y="2.49902" width="8" height="3.76425" rx="1.16774" fill="currentColor" fill-opacity="0.4"></rect><rect x="6.21875" y="6.7334" width="3.78055" height="3.76425" rx="1.16774" fill="currentColor" fill-opacity="0.7"></rect><rect x="2" y="6.73438" width="3.78055" height="3.76425" rx="1.16774" fill="currentColor" fill-opacity="0.5"></rect></svg><!----> Collection</div></header> <div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400"><!--[-1--><!--]--> <span>17 items</span> <span class="px-1.5 text-gray-300">•</span> <span class="truncate">Updated <time datetime="2024-12-13T09:25:04" title="2024-12-13T09:25:04.176Z">Dec 13, 2024</time></span> <!--[0--><span class="px-1.5 text-gray-300">•</span> <!--[-1--><svg class="flex-none w-3 mr-1 text-gray-400" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 12 12" fill="transparent"><path d="M9.30013 9.29152H9.3H2.7H2.69987C2.62308 9.29154 2.54762 9.27146 2.481 9.23328C2.41437 9.1951 2.3589 9.14015 2.32009 9.07389C2.28128 9.00763 2.26048 8.93237 2.25977 8.85558C2.25907 8.7798 2.27796 8.70513 2.31458 8.63882L5.62238 2.9426L5.67518 2.85168C5.7059 2.81806 5.74178 2.78928 5.78164 2.76649C5.84813 2.72848 5.9234 2.70848 6 2.70848C6.0766 2.70848 6.15187 2.72848 6.21836 2.76649C6.28441 2.80425 6.33953 2.85848 6.37836 2.92389L9.68527 8.63855C9.72199 8.70493 9.74093 8.7797 9.74023 8.85558C9.73952 8.93237 9.71872 9.00763 9.67991 9.07389C9.6411 9.14015 9.58563 9.1951 9.519 9.23328C9.45238 9.27146 9.37692 9.29154 9.30013 9.29152Z" stroke="currentColor"></path></svg><!--]--> 620<!--]--></div></a></article> <!--[0--><div class="overview-card-wrapper rounded-md! bg-linear-to-t! -z-1 from-gray-50! to-gray-50! shadow-none! dark:from-gray-925! dark:to-gray-925! -mt-[1.60rem] h-8 scale-x-[98%] transition-transform peer-hover:-translate-y-[2px] peer-hover:from-gray-100/80 dark:peer-hover:from-black"></div><!--]--></div><!--]--></div><!--]--> <!--[0--><div class="divider-column-vertical"></div> <h2 class="text-smd mb-5 flex items-baseline overflow-hidden whitespace-nowrap font-semibold text-gray-800"><svg class="mr-1 inline self-center flex-none text-gray-400" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 12 12" preserveAspectRatio="xMidYMid meet" fill="none"><path fill="currentColor" fill-rule="evenodd" d="M8.007 1.814a1.176 1.176 0 0 0-.732-.266H3.088c-.64 0-1.153.512-1.153 1.152v6.803c0 .64.513 1.152 1.153 1.152h5.54c.632 0 1.144-.511 1.144-1.152V3.816c0-.338-.137-.658-.412-.887L8.007 1.814Zm-1.875 1.81c0 .695.55 1.253 1.244 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"><a href="/papers/2204.05149" class="block p-2"><header class="flex items-center mb-1" title="arxiv:2204.05149"><!--[--><!--]--> <h4 class="truncate font-serif text-black dark:group-hover/paper:text-orange-500 text-smd">The Carbon Footprint of Machine Learning Training Will Plateau, Then1382 Shrink</h4></header> <div class="mr-1 flex items-center overflow-hidden whitespace-nowrap text-sm leading-tight text-gray-400"><svg class="w-3.5 mr-1 flex-none text-gray-400 -translate-y-px" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" viewBox="0 0 12 12" preserveAspectRatio="xMidYMid meet" fill="none"><path fill="currentColor" fill-rule="evenodd" d="M8.007 1.814a1.176 1.176 0 0 0-.732-.266H3.088c-.64 0-1.153.512-1.153 1.152v6.803c0 .64.513 1.152 1.153 1.152h5.54c.632 0 1.144-.511 1.144-1.152V3.816c0-.338-.137-.658-.412-.887L8.007 1.814Zm-1.875 1.81c0 .695.55 1.253 1.244 1.253h.983a.567.567 0 0 1 .553.585v4.041c0 .165-.119.302-.283.302h-5.55c-.156 0-.275-.137-.275-.302V2.7a.284.284 0 0 1 .284-.301h2.468a.574.574 0 0 1 .434.19.567.567 0 0 1 .142.395v.64Z" clip-rule="evenodd" fill-opacity=".8"></path><path fill="currentColor" fill-opacity=".2" fill-rule="evenodd" d="M6.132 3.624c0 .695.55 1.253 1.244 1.253h.97a.567.567 0 0 1 .566.585v4.041c0 .165-.119.302-.283.302h-5.55c-.156 0-.275-.137-.275-.302V2.7a.284.284 0 0 1 .284-.301h2.468a.567.567 0 0 1 .576.585v.64Z" clip-rule="evenodd"></path></svg><!----> Paper <span class="px-1.5 text-gray-300">•</span> 2204.05149 <span class="px-1.5 text-gray-300">•</span> <span class="truncate">Published <time datetime="2022-04-11T14:30:27" title="Mon, 11 Apr 2022 14:30:27 GMT">Apr 11, 2022</time></span> <!--[0--><span class="px-1.5 text-gray-300">•</span> <!--[-1--><svg class="flex-none w-3 mr-1 text-gray-400" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 12 12" fill="transparent"><path d="M9.30013 9.29152H9.3H2.7H2.69987C2.62308 9.29154 2.54762 9.27146 2.481 9.23328C2.41437 9.1951 2.3589 9.14015 2.32009 9.07389C2.28128 9.00763 2.26048 8.93237 2.25977 8.85558C2.25907 8.7798 2.27796 8.70513 2.31458 8.63882L5.62238 2.9426L5.67518 2.85168C5.7059 2.81806 5.74178 2.78928 5.78164 2.76649C5.84813 2.72848 5.9234 2.70848 6 2.70848C6.0766 2.70848 6.15187 2.72848 6.21836 2.76649C6.28441 2.80425 6.33953 2.85848 6.37836 2.92389L9.68527 8.63855C9.72199 8.70493 9.74093 8.7797 9.74023 8.85558C9.73952 8.93237 9.71872 9.00763 9.67991 9.07389C9.6411 9.14015 9.58563 9.1951 9.519 9.23328C9.45238 9.27146 9.37692 9.29154 9.30013 9.29152Z" stroke="currentColor"></path></svg><!--]--> 13<!--]--> <!--[--><!--]--></div></a></article><!--]--></div><!--]--> <!--[-1--><!--]--> <div class="SVELTE_HYDRATER contents" data-target="ModelEvalResults" data-props="{"model":{"author":"meta-llama","cardData":{"language":["en","de","fr","it","pt","hi","es","th"],"license":"llama3.1","base_model":"meta-llama/Meta-Llama-3.1-8B","pipeline_tag":"text-generation","tags":["facebook","meta","pytorch","llama","llama-3"],"extra_gated_prompt":"### LLAMA 3.1 COMMUNITY LICENSE AGREEMENT\nLlama 3.1 Version Release Date: July 23, 2024\n\"Agreement\" means the terms and conditions for use, reproduction, distribution and modification of the Llama Materials set forth herein.\n\"Documentation\" means the specifications, manuals and documentation accompanying Llama 3.1 distributed by Meta at https://llama.meta.com/doc/overview.\n\"Licensee\" or \"you\" means you, or your employer or any other person or entity (if you are entering into this Agreement on such person or entity’s behalf), of the age required under applicable laws, rules or regulations to provide legal consent and that has legal authority to bind your employer or such other person or entity if you are entering in this Agreement on their behalf.\n\"Llama 3.1\" means the foundational large language models and software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Meta at https://llama.meta.com/llama-downloads.\n\"Llama Materials\" means, collectively, Meta’s proprietary Llama 3.1 and Documentation (and any portion thereof) made available under this Agreement.\n\"Meta\" or \"we\" means Meta Platforms Ireland Limited (if you are located in or, if you are an entity, your principal place of business is in the EEA or Switzerland) and Meta Platforms, Inc. 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If you access or use Llama 3.1, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of this policy can be found at [https://llama.meta.com/llama3_1/use-policy](https://llama.meta.com/llama3_1/use-policy)\n#### Prohibited Uses\nWe want everyone to use Llama 3.1 safely and responsibly. You agree you will not use, or allow others to use, Llama 3.1 to:\n 1. Violate the law or others’ rights, including to:\n 1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:\n 1. Violence or terrorism\n 2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material\n 3. Human trafficking, exploitation, and sexual violence\n 4. 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Illegal drugs and regulated/controlled substances\n 4. Operation of critical infrastructure, transportation technologies, or heavy machinery\n 5. Self-harm or harm to others, including suicide, cutting, and eating disorders\n 6. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual\n3. Intentionally deceive or mislead others, including use of Llama 3.1 related to the following:\n 1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation\n 2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content\n 3. Generating, promoting, or further distributing spam\n 4. Impersonating another individual without consent, authorization, or legal right\n 5. Representing that the use of Llama 3.1 or outputs are human-generated\n 6. 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Fail to appropriately disclose to end users any known dangers of your AI system\nPlease report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means:\n * Reporting issues with the model: [https://github.com/meta-llama/llama-models/issues](https://github.com/meta-llama/llama-models/issues)\n * Reporting risky content generated by the model:\n developers.facebook.com/llama_output_feedback\n * Reporting bugs and security concerns: facebook.com/whitehat/info\n * Reporting violations of the Acceptable Use Policy or unlicensed uses of Meta Llama 3: LlamaUseReport@meta.com","extra_gated_fields":{"First Name":"text","Last Name":"text","Date of birth":"date_picker","Country":"country","Affiliation":"text","Job title":{"type":"select","options":["Student","Research Graduate","AI researcher","AI developer/engineer","Reporter","Other"]},"geo":"ip_location","By clicking Submit below I accept the terms of the license and acknowledge that the information I provide will be collected stored processed and shared in accordance with the Meta Privacy Policy":"checkbox"},"extra_gated_description":"The information you provide will be collected, stored, processed and shared in accordance with the [Meta Privacy Policy](https://www.facebook.com/privacy/policy/).","extra_gated_button_content":"Submit"},"cardExists":true,"config":{"architectures":["LlamaForCausalLM"],"model_type":"llama","tokenizer_config":{"bos_token":"<|begin_of_text|>","chat_template":"{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. 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<!--[0--><span class="relative font-mono text-xs">0.5 <sup class="absolute -right-2 top-px text-[0.675rem] font-normal text-blue-700 dark:text-blue-500">*</sup></span><!--]--></div><!----></li><!--]--><!--]--> <!--[0--><li class="flex items-center gap-1.5"><div class="-translate-y-0.75 w-3.75 relative mr-0.5 h-5 flex-none"><!--[-1--><!--]--> <!--[0--><svg class="text-gray-300 dark:text-gray-700" width="15" height="28" viewBox="0 0 15 28" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M0.967742 0C0.967742 7.67991 7.21819 13.9655 15 13.9655V15C6.74768 15 0 8.3173 0 0H0.967742Z" fill="currentColor"></path></svg><!--]--></div><!----> <button class="text-gray-500 hover:text-gray-700 dark:text-gray-400 dark:hover:text-gray-200">+3 more</button></li><!--]--><!--]--><!--]--> <!--[--><li class="flex items-center gap-x-1 text-gray-500 hover:bg-gray-50/50 has-[a:hover]:bg-transparent dark:text-gray-400 dark:hover:bg-gray-900/50 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