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Co-authored-by: Bartowski <[email protected]>

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+ ---
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+ language:
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+ - en
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+ pipeline_tag: text-generation
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+ tags:
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+ - facebook
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+ - meta
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+ - pytorch
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+ - llama
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+ - llama-3
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+ license: other
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+ license_name: llama3
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+ license_link: LICENSE
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+ extra_gated_prompt: >-
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+ ### META LLAMA 3 COMMUNITY LICENSE AGREEMENT
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+
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+ Meta Llama 3 Version Release Date: April 18, 2024
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+
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+ "Agreement" means the terms and conditions for use, reproduction, distribution and modification of the
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+ Llama Materials set forth herein.
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+
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+ "Documentation" means the specifications, manuals and documentation accompanying Meta Llama 3
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+ distributed by Meta at https://llama.meta.com/get-started/.
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+
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+ "Licensee" or "you" means you, or your employer or any other person or entity (if you are entering into
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+ this Agreement on such person or entity’s behalf), of the age required under applicable laws, rules or
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+ regulations to provide legal consent and that has legal authority to bind your employer or such other
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+ person or entity if you are entering in this Agreement on their behalf.
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+
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+ "Meta Llama 3" means the foundational large language models and software and algorithms, including
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+ machine-learning model code, trained model weights, inference-enabling code, training-enabling code,
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+ fine-tuning enabling code and other elements of the foregoing distributed by Meta at
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+ https://llama.meta.com/llama-downloads.
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+
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+ "Llama Materials" means, collectively, Meta’s proprietary Meta Llama 3 and Documentation (and any
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+ portion thereof) made available under this Agreement.
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+
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+
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+ v. You will not use the Llama Materials or any output or results of the Llama Materials to
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+ improve any other large language model (excluding Meta Llama 3 or derivative works thereof).
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+
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+ 2. Additional Commercial Terms. If, on the Meta Llama 3 version release date, the monthly active users
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+ million monthly active users in the preceding calendar month, you must request a license from Meta,
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+
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+ 3. Disclaimer of Warranty. UNLESS REQUIRED BY APPLICABLE LAW, THE LLAMA MATERIALS AND ANY
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+ a. No trademark licenses are granted under this Agreement, and in connection with the Llama
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+ exclusive jurisdiction of any dispute arising out of this Agreement.
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+
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+ ### Meta Llama 3 Acceptable Use Policy
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+
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+ Meta is committed to promoting safe and fair use of its tools and features, including Meta Llama 3. If you
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+ access or use Meta Llama 3, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of
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+ this policy can be found at [https://llama.meta.com/llama3/use-policy](https://llama.meta.com/llama3/use-policy)
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+
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+ #### Prohibited Uses
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+
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+ We want everyone to use Meta Llama 3 safely and responsibly. You agree you will not use, or allow
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+ others to use, Meta Llama 3 to:
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+ 1. Violate the law or others’ rights, including to:
142
+ 1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:
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+ 1. Violence or terrorism
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+ 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
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+ 3. Human trafficking, exploitation, and sexual violence
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+ 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.
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+ 5. Sexual solicitation
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+ 6. Any other criminal activity
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+ 2. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
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+ 3. 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
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+ 4. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices
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+ 5. 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
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+ 6. 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
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+ 7. 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
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+ 2. 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 Meta Llama 3 related to the following:
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+ 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
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+ 2. Guns and illegal weapons (including weapon development)
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+ 3. Illegal drugs and regulated/controlled substances
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+ 4. Operation of critical infrastructure, transportation technologies, or heavy machinery
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+ 5. Self-harm or harm to others, including suicide, cutting, and eating disorders
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+ 6. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
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+ 3. Intentionally deceive or mislead others, including use of Meta Llama 3 related to the following:
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+ 1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
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+ 2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
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+ 3. Generating, promoting, or further distributing spam
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+ 4. Impersonating another individual without consent, authorization, or legal right
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+ 5. Representing that the use of Meta Llama 3 or outputs are human-generated
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+ 6. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement
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+ 4. Fail to appropriately disclose to end users any known dangers of your AI system
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+
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+ Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation
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+ of this Policy through one of the following means:
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+ * Reporting issues with the model: [https://github.com/meta-llama/llama3](https://github.com/meta-llama/llama3)
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+ * Reporting risky content generated by the model:
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+ developers.facebook.com/llama_output_feedback
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+ * Reporting bugs and security concerns: facebook.com/whitehat/info
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+ * Reporting violations of the Acceptable Use Policy or unlicensed uses of Meta Llama 3: [email protected]
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+ extra_gated_fields:
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+ First Name: text
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+ Last Name: text
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+ Date of birth: date_picker
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+ Country: country
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+ Affiliation: text
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+ geo: ip_location
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+ 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
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+ 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/).
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+ extra_gated_button_content: Submit
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+ quantized_by: bartowski
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+ ---
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+
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+ ## Llamacpp Quantizations of Meta-Llama-3-70B-Instruct
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+
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+ Since official Llama 3 support has arrived to llama.cpp release, I will be remaking this entirely and uploading as soon as it's done.
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+
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+ This model has the <|eot_id|> token set to not-special, which seems to work better with current inference engines.
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+
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+ Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> fork from pcuenca <a href="https://github.com/pcuenca/llama.cpp/tree/llama3-conversion">llama3-conversion</a> for quantization.
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+
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+ Original model: https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct
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+
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+ ## Prompt format
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+
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+ ```
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+ <|begin_of_text|><|start_header_id|>system<|end_header_id|>
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+
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+ {system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
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+
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+ {prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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+
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+
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+ ```
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+
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+ ## Download a file (not the whole branch) from below:
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+
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+ | Filename | Quant type | File Size | Description |
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+ | -------- | ---------- | --------- | ----------- |
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+ | [Meta-Llama-3-70B-Instruct-Q5_K_M.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-Q5_K_M.gguf) | Q5_K_M | 49.94GB | High quality, *recommended*. |
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+ | [Meta-Llama-3-70B-Instruct-Q5_K_S.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-Q5_K_S.gguf) | Q5_K_S | 48.65GB | High quality, *recommended*. |
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+ | [Meta-Llama-3-70B-Instruct-Q4_K_M.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-Q4_K_M.gguf) | Q4_K_M | 42.52GB | Good quality, uses about 4.83 bits per weight, *recommended*. |
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+ | [Meta-Llama-3-70B-Instruct-Q4_K_S.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-Q4_K_S.gguf) | Q4_K_S | 40.34GB | Slightly lower quality with more space savings, *recommended*. |
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+ | [Meta-Llama-3-70B-Instruct-IQ4_NL.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-IQ4_NL.gguf) | IQ4_NL | 40.34GB | Decent quality, slightly smaller than Q4_K_S with similar performance *recommended*. |
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+ | [Meta-Llama-3-70B-Instruct-IQ4_XS.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-IQ4_XS.gguf) | IQ4_XS | 38.26GB | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
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+ | [Meta-Llama-3-70B-Instruct-Q3_K_L.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-Q3_K_L.gguf) | Q3_K_L | 37.14GB | Lower quality but usable, good for low RAM availability. |
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+ | [Meta-Llama-3-70B-Instruct-Q3_K_M.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-Q3_K_M.gguf) | Q3_K_M | 34.26GB | Even lower quality. |
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+ | [Meta-Llama-3-70B-Instruct-IQ3_M.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-IQ3_M.gguf) | IQ3_M | 31.93GB | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
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+ | [Meta-Llama-3-70B-Instruct-IQ3_S.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-IQ3_S.gguf) | IQ3_S | 30.91GB | Lower quality, new method with decent performance, recommended over Q3_K_S quant, same size with better performance. |
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+ | [Meta-Llama-3-70B-Instruct-Q3_K_S.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-Q3_K_S.gguf) | Q3_K_S | 30.91GB | Low quality, not recommended. |
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+ | [Meta-Llama-3-70B-Instruct-IQ3_XS.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-IQ3_XS.gguf) | IQ3_XS | 29.30GB | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
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+ | [Meta-Llama-3-70B-Instruct-Q2_K.gguf](https://huggingface.co/bartowski/Meta-Llama-3-70B-Instruct-GGUF/blob/main/Meta-Llama-3-70B-Instruct-Q2_K.gguf) | Q2_K | 26.37GB | Very low quality but surprisingly usable. |
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+
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+ ## Which file should I choose?
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+
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+ A great write up with charts showing various performances is provided by Artefact2 [here](https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9)
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+
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+ The first thing to figure out is how big a model you can run. To do this, you'll need to figure out how much RAM and/or VRAM you have.
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+
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+ If you want your model running as FAST as possible, you'll want to fit the whole thing on your GPU's VRAM. Aim for a quant with a file size 1-2GB smaller than your GPU's total VRAM.
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+
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+ If you want the absolute maximum quality, add both your system RAM and your GPU's VRAM together, then similarly grab a quant with a file size 1-2GB Smaller than that total.
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+
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+ Next, you'll need to decide if you want to use an 'I-quant' or a 'K-quant'.
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+
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+ If you don't want to think too much, grab one of the K-quants. These are in format 'QX_K_X', like Q5_K_M.
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+
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+ If you want to get more into the weeds, you can check out this extremely useful feature chart:
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+
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+ [llama.cpp feature matrix](https://github.com/ggerganov/llama.cpp/wiki/Feature-matrix)
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+
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+ But basically, if you're aiming for below Q4, and you're running cuBLAS (Nvidia) or rocBLAS (AMD), you should look towards the I-quants. These are in format IQX_X, like IQ3_M. These are newer and offer better performance for their size.
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+
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+ These I-quants can also be used on CPU and Apple Metal, but will be slower than their K-quant equivalent, so speed vs performance is a tradeoff you'll have to decide.
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+
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+ The I-quants are *not* compatible with Vulcan, which is also AMD, so if you have an AMD card double check if you're using the rocBLAS build or the Vulcan build. At the time of writing this, LM Studio has a preview with ROCm support, and other inference engines have specific builds for ROCm.
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+
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+ Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski