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Model: legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF Source: Original Platform
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---
|
||||
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
|
||||
extra_gated_button_content: Submit
|
||||
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_fields:
|
||||
Affiliation: text
|
||||
? 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
|
||||
Country: country
|
||||
Date of birth: date_picker
|
||||
First Name: text
|
||||
Job title:
|
||||
options:
|
||||
- Student
|
||||
- Research Graduate
|
||||
- AI researcher
|
||||
- AI developer/engineer
|
||||
- Reporter
|
||||
- Other
|
||||
type: select
|
||||
Last Name: text
|
||||
geo: ip_location
|
||||
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\u2019s 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\u2019s 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.\n\
|
||||
a. Grant of Rights. You are granted a non-exclusive, worldwide, non-transferable\
|
||||
\ and royalty-free limited license under Meta\u2019s 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.\n\
|
||||
b. 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 \u201CBuilt with Llama\u201D\
|
||||
\ 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 \u201CLlama\u201D 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 \u201CNotice\u201D text file distributed as a part of such copies: \u201C\
|
||||
Llama 3.1 is licensed under the Llama 3.1 Community License, Copyright \xA9 Meta\
|
||||
\ Platforms, Inc. All Rights Reserved.\u201D\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\u2019s 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 \u201CAS IS\u201D 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.\n\
|
||||
4. 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.\n\
|
||||
5. 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 \u201CLlama\u201D (the \u201CMark\u201D) solely as required to\
|
||||
\ comply with the last sentence of Section 1.b.i. You will comply with Meta\u2019\
|
||||
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\u2019s 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\n\
|
||||
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\
|
||||
\ (\u201CPolicy\u201D). 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\u2019 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 \u201Cbug,\u201D 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"
|
||||
inference: false
|
||||
language:
|
||||
- en
|
||||
- de
|
||||
- fr
|
||||
- it
|
||||
- pt
|
||||
- hi
|
||||
- es
|
||||
- th
|
||||
library_name: gguf
|
||||
license: llama3.1
|
||||
pipeline_tag: text-generation
|
||||
quantized_by: legraphista
|
||||
tags:
|
||||
- facebook
|
||||
- meta
|
||||
- pytorch
|
||||
- llama
|
||||
- llama-3
|
||||
- quantized
|
||||
- GGUF
|
||||
- quantization
|
||||
- imat
|
||||
- imatrix
|
||||
- static
|
||||
- 16bit
|
||||
- 8bit
|
||||
- 6bit
|
||||
- 5bit
|
||||
- 4bit
|
||||
- 3bit
|
||||
- 2bit
|
||||
- 1bit
|
||||
---
|
||||
|
||||
> [!NOTE]
|
||||
> If you're looking for quants pre [llama.cpp PR #8676](https://github.com/ggerganov/llama.cpp/pull/8676), you can find them here [in this branch](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/tree/pre-llama.cpp-fix)
|
||||
> Main branch quants may not be not compatible with older llama.cpp builds
|
||||
|
||||
# Meta-Llama-3.1-8B-Instruct-IMat-GGUF
|
||||
_Llama.cpp imatrix quantization of meta-llama/Meta-Llama-3.1-8B-Instruct_
|
||||
|
||||
Original Model: [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct)
|
||||
Original dtype: `BF16` (`bfloat16`)
|
||||
Quantized by: llama.cpp [b3479](https://github.com/ggerganov/llama.cpp/releases/tag/b3479)
|
||||
IMatrix dataset: [here](https://gist.githubusercontent.com/bartowski1182/eb213dccb3571f863da82e99418f81e8/raw/b2869d80f5c16fd7082594248e80144677736635/calibration_datav3.txt)
|
||||
|
||||
- [Files](#files)
|
||||
- [IMatrix](#imatrix)
|
||||
- [Common Quants](#common-quants)
|
||||
- [All Quants](#all-quants)
|
||||
- [Downloading using huggingface-cli](#downloading-using-huggingface-cli)
|
||||
- [Inference](#inference)
|
||||
- [Simple chat template](#simple-chat-template)
|
||||
- [Chat template with system prompt](#chat-template-with-system-prompt)
|
||||
- [Llama.cpp](#llama-cpp)
|
||||
- [FAQ](#faq)
|
||||
- [Why is the IMatrix not applied everywhere?](#why-is-the-imatrix-not-applied-everywhere)
|
||||
- [How do I merge a split GGUF?](#how-do-i-merge-a-split-gguf)
|
||||
|
||||
---
|
||||
|
||||
## Files
|
||||
|
||||
### IMatrix
|
||||
Status: ✅ Available
|
||||
Link: [here](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/imatrix.dat)
|
||||
|
||||
### Common Quants
|
||||
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
|
||||
| -------- | ---------- | --------- | ------ | ------------ | -------- |
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q8_0.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q8_0.gguf) | Q8_0 | 8.54GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q6_K.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q6_K.gguf) | Q6_K | 6.60GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q4_K.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q4_K.gguf) | Q4_K | 4.92GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q3_K.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q3_K.gguf) | Q3_K | 4.02GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q2_K.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q2_K.gguf) | Q2_K | 3.18GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
|
||||
|
||||
### All Quants
|
||||
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
|
||||
| -------- | ---------- | --------- | ------ | ------------ | -------- |
|
||||
| [Meta-Llama-3.1-8B-Instruct.BF16.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.BF16.gguf) | BF16 | 16.07GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.FP16.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.FP16.gguf) | F16 | 16.07GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q8_0.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q8_0.gguf) | Q8_0 | 8.54GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q6_K.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q6_K.gguf) | Q6_K | 6.60GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q5_K.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q5_K.gguf) | Q5_K | 5.73GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q5_K_S.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q5_K_S.gguf) | Q5_K_S | 5.60GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q4_K.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q4_K.gguf) | Q4_K | 4.92GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q4_K_S.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q4_K_S.gguf) | Q4_K_S | 4.69GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.IQ4_NL.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.IQ4_NL.gguf) | IQ4_NL | 4.68GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.IQ4_XS.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.IQ4_XS.gguf) | IQ4_XS | 4.45GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q3_K.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q3_K.gguf) | Q3_K | 4.02GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q3_K_L.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q3_K_L.gguf) | Q3_K_L | 4.32GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q3_K_S.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q3_K_S.gguf) | Q3_K_S | 3.66GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.IQ3_M.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.IQ3_M.gguf) | IQ3_M | 3.78GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.IQ3_S.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.IQ3_S.gguf) | IQ3_S | 3.68GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.IQ3_XS.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.IQ3_XS.gguf) | IQ3_XS | 3.52GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.IQ3_XXS.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.IQ3_XXS.gguf) | IQ3_XXS | 3.27GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q2_K.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q2_K.gguf) | Q2_K | 3.18GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.Q2_K_S.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.Q2_K_S.gguf) | Q2_K_S | 2.99GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.IQ2_M.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.IQ2_M.gguf) | IQ2_M | 2.95GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.IQ2_S.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.IQ2_S.gguf) | IQ2_S | 2.76GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.IQ2_XS.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.IQ2_XS.gguf) | IQ2_XS | 2.61GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.IQ2_XXS.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.IQ2_XXS.gguf) | IQ2_XXS | 2.40GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.IQ1_M.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.IQ1_M.gguf) | IQ1_M | 2.16GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Meta-Llama-3.1-8B-Instruct.IQ1_S.gguf](https://huggingface.co/legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF/blob/main/Meta-Llama-3.1-8B-Instruct.IQ1_S.gguf) | IQ1_S | 2.02GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
|
||||
|
||||
## Downloading using huggingface-cli
|
||||
If you do not have hugginface-cli installed:
|
||||
```
|
||||
pip install -U "huggingface_hub[cli]"
|
||||
```
|
||||
Download the specific file you want:
|
||||
```
|
||||
huggingface-cli download legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF --include "Meta-Llama-3.1-8B-Instruct.Q8_0.gguf" --local-dir ./
|
||||
```
|
||||
If the model file is big, it has been split into multiple files. In order to download them all to a local folder, run:
|
||||
```
|
||||
huggingface-cli download legraphista/Meta-Llama-3.1-8B-Instruct-IMat-GGUF --include "Meta-Llama-3.1-8B-Instruct.Q8_0/*" --local-dir ./
|
||||
# see FAQ for merging GGUF's
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Inference
|
||||
|
||||
### Simple chat template
|
||||
```
|
||||
<|begin_of_text|><|start_header_id|>user<|end_header_id|>
|
||||
|
||||
{user_prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
|
||||
|
||||
{assistant_response}<|eot_id|><|start_header_id|>user<|end_header_id|>
|
||||
|
||||
{next_user_prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
|
||||
|
||||
|
||||
```
|
||||
|
||||
### Chat template with system prompt
|
||||
```
|
||||
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
|
||||
|
||||
{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
|
||||
|
||||
{user_prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
|
||||
|
||||
{assistant_response}<|eot_id|><|start_header_id|>user<|end_header_id|>
|
||||
|
||||
{next_user_prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
|
||||
|
||||
|
||||
```
|
||||
|
||||
### Llama.cpp
|
||||
```
|
||||
llama.cpp/main -m Meta-Llama-3.1-8B-Instruct.Q8_0.gguf --color -i -p "prompt here (according to the chat template)"
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## FAQ
|
||||
|
||||
### Why is the IMatrix not applied everywhere?
|
||||
According to [this investigation](https://www.reddit.com/r/LocalLLaMA/comments/1993iro/ggufs_quants_can_punch_above_their_weights_now/), it appears that lower quantizations are the only ones that benefit from the imatrix input (as per hellaswag results).
|
||||
|
||||
### How do I merge a split GGUF?
|
||||
1. Make sure you have `gguf-split` available
|
||||
- To get hold of `gguf-split`, navigate to https://github.com/ggerganov/llama.cpp/releases
|
||||
- Download the appropriate zip for your system from the latest release
|
||||
- Unzip the archive and you should be able to find `gguf-split`
|
||||
2. Locate your GGUF chunks folder (ex: `Meta-Llama-3.1-8B-Instruct.Q8_0`)
|
||||
3. Run `gguf-split --merge Meta-Llama-3.1-8B-Instruct.Q8_0/Meta-Llama-3.1-8B-Instruct.Q8_0-00001-of-XXXXX.gguf Meta-Llama-3.1-8B-Instruct.Q8_0.gguf`
|
||||
- Make sure to point `gguf-split` to the first chunk of the split.
|
||||
|
||||
---
|
||||
|
||||
Got a suggestion? Ping me [@legraphista](https://x.com/legraphista)!
|
||||
3
imatrix.dat
Normal file
3
imatrix.dat
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:e241bb4d3108cb8e1d458ed151480552d27ccb9acbb8f2888531717a588edb44
|
||||
size 4988186
|
||||
2482
imatrix.dataset
Normal file
2482
imatrix.dataset
Normal file
File diff suppressed because one or more lines are too long
147
imatrix.log
Normal file
147
imatrix.log
Normal file
@@ -0,0 +1,147 @@
|
||||
llama_model_loader: loaded meta data with 29 key-value pairs and 292 tensors from Meta-Llama-3.1-8B-Instruct-IMat-GGUF/Meta-Llama-3.1-8B-Instruct.Q8_0.gguf.hardlink.gguf (version GGUF V3 (latest))
|
||||
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
|
||||
llama_model_loader: - kv 0: general.architecture str = llama
|
||||
llama_model_loader: - kv 1: general.type str = model
|
||||
llama_model_loader: - kv 2: general.name str = Meta Llama 3.1 8B Instruct
|
||||
llama_model_loader: - kv 3: general.finetune str = Instruct
|
||||
llama_model_loader: - kv 4: general.basename str = Meta-Llama-3.1
|
||||
llama_model_loader: - kv 5: general.size_label str = 8B
|
||||
llama_model_loader: - kv 6: general.license str = llama3.1
|
||||
llama_model_loader: - kv 7: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam...
|
||||
llama_model_loader: - kv 8: general.languages arr[str,8] = ["en", "de", "fr", "it", "pt", "hi", ...
|
||||
llama_model_loader: - kv 9: llama.block_count u32 = 32
|
||||
llama_model_loader: - kv 10: llama.context_length u32 = 131072
|
||||
llama_model_loader: - kv 11: llama.embedding_length u32 = 4096
|
||||
llama_model_loader: - kv 12: llama.feed_forward_length u32 = 14336
|
||||
llama_model_loader: - kv 13: llama.attention.head_count u32 = 32
|
||||
llama_model_loader: - kv 14: llama.attention.head_count_kv u32 = 8
|
||||
llama_model_loader: - kv 15: llama.rope.freq_base f32 = 500000.000000
|
||||
llama_model_loader: - kv 16: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
|
||||
llama_model_loader: - kv 17: general.file_type u32 = 7
|
||||
llama_model_loader: - kv 18: llama.vocab_size u32 = 128256
|
||||
llama_model_loader: - kv 19: llama.rope.dimension_count u32 = 128
|
||||
llama_model_loader: - kv 20: tokenizer.ggml.model str = gpt2
|
||||
llama_model_loader: - kv 21: tokenizer.ggml.pre str = llama-bpe
|
||||
llama_model_loader: - kv 22: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ...
|
||||
llama_model_loader: - kv 23: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
|
||||
llama_model_loader: - kv 24: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
|
||||
llama_model_loader: - kv 25: tokenizer.ggml.bos_token_id u32 = 128000
|
||||
llama_model_loader: - kv 26: tokenizer.ggml.eos_token_id u32 = 128009
|
||||
llama_model_loader: - kv 27: tokenizer.chat_template str = {% set loop_messages = messages %}{% ...
|
||||
llama_model_loader: - kv 28: general.quantization_version u32 = 2
|
||||
llama_model_loader: - type f32: 66 tensors
|
||||
llama_model_loader: - type q8_0: 226 tensors
|
||||
llm_load_vocab: special tokens cache size = 256
|
||||
llm_load_vocab: token to piece cache size = 0.7999 MB
|
||||
llm_load_print_meta: format = GGUF V3 (latest)
|
||||
llm_load_print_meta: arch = llama
|
||||
llm_load_print_meta: vocab type = BPE
|
||||
llm_load_print_meta: n_vocab = 128256
|
||||
llm_load_print_meta: n_merges = 280147
|
||||
llm_load_print_meta: vocab_only = 0
|
||||
llm_load_print_meta: n_ctx_train = 131072
|
||||
llm_load_print_meta: n_embd = 4096
|
||||
llm_load_print_meta: n_layer = 32
|
||||
llm_load_print_meta: n_head = 32
|
||||
llm_load_print_meta: n_head_kv = 8
|
||||
llm_load_print_meta: n_rot = 128
|
||||
llm_load_print_meta: n_swa = 0
|
||||
llm_load_print_meta: n_embd_head_k = 128
|
||||
llm_load_print_meta: n_embd_head_v = 128
|
||||
llm_load_print_meta: n_gqa = 4
|
||||
llm_load_print_meta: n_embd_k_gqa = 1024
|
||||
llm_load_print_meta: n_embd_v_gqa = 1024
|
||||
llm_load_print_meta: f_norm_eps = 0.0e+00
|
||||
llm_load_print_meta: f_norm_rms_eps = 1.0e-05
|
||||
llm_load_print_meta: f_clamp_kqv = 0.0e+00
|
||||
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
|
||||
llm_load_print_meta: f_logit_scale = 0.0e+00
|
||||
llm_load_print_meta: n_ff = 14336
|
||||
llm_load_print_meta: n_expert = 0
|
||||
llm_load_print_meta: n_expert_used = 0
|
||||
llm_load_print_meta: causal attn = 1
|
||||
llm_load_print_meta: pooling type = 0
|
||||
llm_load_print_meta: rope type = 0
|
||||
llm_load_print_meta: rope scaling = linear
|
||||
llm_load_print_meta: freq_base_train = 500000.0
|
||||
llm_load_print_meta: freq_scale_train = 1
|
||||
llm_load_print_meta: n_ctx_orig_yarn = 131072
|
||||
llm_load_print_meta: rope_finetuned = unknown
|
||||
llm_load_print_meta: ssm_d_conv = 0
|
||||
llm_load_print_meta: ssm_d_inner = 0
|
||||
llm_load_print_meta: ssm_d_state = 0
|
||||
llm_load_print_meta: ssm_dt_rank = 0
|
||||
llm_load_print_meta: model type = 8B
|
||||
llm_load_print_meta: model ftype = Q8_0
|
||||
llm_load_print_meta: model params = 8.03 B
|
||||
llm_load_print_meta: model size = 7.95 GiB (8.50 BPW)
|
||||
llm_load_print_meta: general.name = Meta Llama 3.1 8B Instruct
|
||||
llm_load_print_meta: BOS token = 128000 '<|begin_of_text|>'
|
||||
llm_load_print_meta: EOS token = 128009 '<|eot_id|>'
|
||||
llm_load_print_meta: LF token = 128 'Ä'
|
||||
llm_load_print_meta: EOT token = 128009 '<|eot_id|>'
|
||||
llm_load_print_meta: max token length = 256
|
||||
ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
|
||||
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
|
||||
ggml_cuda_init: found 1 CUDA devices:
|
||||
Device 0: NVIDIA GeForce RTX 4090, compute capability 8.9, VMM: yes
|
||||
llm_load_tensors: ggml ctx size = 0.27 MiB
|
||||
llm_load_tensors: offloading 32 repeating layers to GPU
|
||||
llm_load_tensors: offloading non-repeating layers to GPU
|
||||
llm_load_tensors: offloaded 33/33 layers to GPU
|
||||
llm_load_tensors: CPU buffer size = 532.31 MiB
|
||||
llm_load_tensors: CUDA0 buffer size = 7605.34 MiB
|
||||
.........................................................................................
|
||||
llama_new_context_with_model: n_ctx = 512
|
||||
llama_new_context_with_model: n_batch = 512
|
||||
llama_new_context_with_model: n_ubatch = 512
|
||||
llama_new_context_with_model: flash_attn = 0
|
||||
llama_new_context_with_model: freq_base = 500000.0
|
||||
llama_new_context_with_model: freq_scale = 1
|
||||
llama_kv_cache_init: CUDA0 KV buffer size = 64.00 MiB
|
||||
llama_new_context_with_model: KV self size = 64.00 MiB, K (f16): 32.00 MiB, V (f16): 32.00 MiB
|
||||
llama_new_context_with_model: CUDA_Host output buffer size = 0.49 MiB
|
||||
llama_new_context_with_model: CUDA0 compute buffer size = 258.50 MiB
|
||||
llama_new_context_with_model: CUDA_Host compute buffer size = 9.01 MiB
|
||||
llama_new_context_with_model: graph nodes = 1030
|
||||
llama_new_context_with_model: graph splits = 2
|
||||
|
||||
system_info: n_threads = 25 / 32 | AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | AVX512_BF16 = 1 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 |
|
||||
compute_imatrix: tokenizing the input ..
|
||||
compute_imatrix: tokenization took 40.567 ms
|
||||
compute_imatrix: computing over 125 chunks with batch_size 512
|
||||
compute_imatrix: 0.67 seconds per pass - ETA 1.40 minutes
|
||||
[1]5.6450,[2]4.4702,[3]4.0740,[4]5.0229,[5]5.2037,[6]4.4021,[7]4.6701,[8]5.1378,[9]5.3205,
|
||||
save_imatrix: stored collected data after 10 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[10]4.8485,[11]5.2853,[12]5.7849,[13]6.2502,[14]6.6483,[15]6.9530,[16]7.2090,[17]7.3963,[18]7.1322,[19]6.8074,
|
||||
save_imatrix: stored collected data after 20 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[20]6.7943,[21]6.9043,[22]6.8396,[23]7.1398,[24]7.1030,[25]7.4353,[26]7.4332,[27]7.4675,[28]7.7040,[29]7.7057,
|
||||
save_imatrix: stored collected data after 30 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[30]7.6655,[31]7.2633,[32]6.8970,[33]6.7255,[34]6.5763,[35]6.6251,[36]6.6641,[37]6.5966,[38]6.6691,[39]6.8314,
|
||||
save_imatrix: stored collected data after 40 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[40]6.9164,[41]6.9534,[42]7.0537,[43]7.2634,[44]7.3427,[45]7.5240,[46]7.4093,[47]7.5276,[48]7.6077,[49]7.7031,
|
||||
save_imatrix: stored collected data after 50 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[50]7.5974,[51]7.6994,[52]7.8264,[53]7.9057,[54]7.9634,[55]8.0354,[56]8.0725,[57]8.1231,[58]8.1399,[59]8.1486,
|
||||
save_imatrix: stored collected data after 60 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[60]8.1036,[61]8.0840,[62]8.1257,[63]8.1674,[64]8.0841,[65]8.0472,[66]8.0453,[67]8.0126,[68]7.9960,[69]7.9754,
|
||||
save_imatrix: stored collected data after 70 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[70]7.9684,[71]7.9568,[72]7.9475,[73]7.9085,[74]7.8517,[75]7.8432,[76]7.8412,[77]7.7991,[78]7.7869,[79]7.8144,
|
||||
save_imatrix: stored collected data after 80 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[80]7.8355,[81]7.8187,[82]7.8068,[83]7.8325,[84]7.7284,[85]7.7280,[86]7.7349,[87]7.7448,[88]7.7729,[89]7.7736,
|
||||
save_imatrix: stored collected data after 90 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[90]7.7163,[91]7.6404,[92]7.5762,[93]7.5210,[94]7.4600,[95]7.4064,[96]7.3665,[97]7.3742,[98]7.4158,[99]7.5038,
|
||||
save_imatrix: stored collected data after 100 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[100]7.5790,[101]7.6302,[102]7.7523,[103]7.7770,[104]7.8144,[105]7.7421,[106]7.7473,[107]7.6992,[108]7.6483,[109]7.5837,
|
||||
save_imatrix: stored collected data after 110 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[110]7.6274,[111]7.6830,[112]7.6914,[113]7.6846,[114]7.7188,[115]7.7524,[116]7.7605,[117]7.7820,[118]7.8124,[119]7.7604,
|
||||
save_imatrix: stored collected data after 120 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
[120]7.7775,[121]7.7835,[122]7.8095,[123]7.8550,[124]7.8913,[125]7.9140,
|
||||
save_imatrix: stored collected data after 125 chunks in Meta-Llama-3.1-8B-Instruct-IMat-GGUF/imatrix.dat
|
||||
|
||||
llama_print_timings: load time = 2039.67 ms
|
||||
llama_print_timings: sample time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second)
|
||||
llama_print_timings: prompt eval time = 71215.49 ms / 64000 tokens ( 1.11 ms per token, 898.68 tokens per second)
|
||||
llama_print_timings: eval time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second)
|
||||
llama_print_timings: total time = 73402.48 ms / 64001 tokens
|
||||
|
||||
Final estimate: PPL = 7.9140 +/- 0.11223
|
||||
Reference in New Issue
Block a user