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Model: legraphista/Llama-Guard-3-8B-IMat-GGUF Source: Original Platform
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351
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---
|
||||
base_model: meta-llama/Llama-Guard-3-8B
|
||||
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\
|
||||
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|
||||
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|
||||
\ 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\
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
\ 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\
|
||||
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|
||||
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|
||||
\ of this Agreement, you shall delete and cease use of the Llama Materials. Sections\
|
||||
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|
||||
\ 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\
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||||
\ 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
|
||||
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
|
||||
---
|
||||
|
||||
# Llama-Guard-3-8B-IMat-GGUF
|
||||
_Llama.cpp imatrix quantization of meta-llama/Llama-Guard-3-8B_
|
||||
|
||||
Original Model: [meta-llama/Llama-Guard-3-8B](https://huggingface.co/meta-llama/Llama-Guard-3-8B)
|
||||
Original dtype: `BF16` (`bfloat16`)
|
||||
Quantized by: llama.cpp [b3447](https://github.com/ggerganov/llama.cpp/releases/tag/b3447)
|
||||
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)
|
||||
- [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/Llama-Guard-3-8B-IMat-GGUF/blob/main/imatrix.dat)
|
||||
|
||||
### Common Quants
|
||||
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
|
||||
| -------- | ---------- | --------- | ------ | ------------ | -------- |
|
||||
| [Llama-Guard-3-8B.Q8_0.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q8_0.gguf) | Q8_0 | 8.54GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Llama-Guard-3-8B.Q6_K.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q6_K.gguf) | Q6_K | 6.60GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Llama-Guard-3-8B.Q4_K.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q4_K.gguf) | Q4_K | 4.92GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.Q3_K.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q3_K.gguf) | Q3_K | 4.02GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.Q2_K.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q2_K.gguf) | Q2_K | 3.18GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
|
||||
|
||||
### All Quants
|
||||
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
|
||||
| -------- | ---------- | --------- | ------ | ------------ | -------- |
|
||||
| [Llama-Guard-3-8B.BF16.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.BF16.gguf) | BF16 | 16.07GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Llama-Guard-3-8B.FP16.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.FP16.gguf) | F16 | 16.07GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Llama-Guard-3-8B.Q8_0.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q8_0.gguf) | Q8_0 | 8.54GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Llama-Guard-3-8B.Q6_K.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q6_K.gguf) | Q6_K | 6.60GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Llama-Guard-3-8B.Q5_K.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q5_K.gguf) | Q5_K | 5.73GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Llama-Guard-3-8B.Q5_K_S.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q5_K_S.gguf) | Q5_K_S | 5.60GB | ✅ Available | ⚪ Static | 📦 No
|
||||
| [Llama-Guard-3-8B.Q4_K.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q4_K.gguf) | Q4_K | 4.92GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.Q4_K_S.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q4_K_S.gguf) | Q4_K_S | 4.69GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.IQ4_NL.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.IQ4_NL.gguf) | IQ4_NL | 4.68GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.IQ4_XS.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.IQ4_XS.gguf) | IQ4_XS | 4.45GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.Q3_K.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q3_K.gguf) | Q3_K | 4.02GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.Q3_K_L.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q3_K_L.gguf) | Q3_K_L | 4.32GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.Q3_K_S.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q3_K_S.gguf) | Q3_K_S | 3.66GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.IQ3_M.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.IQ3_M.gguf) | IQ3_M | 3.78GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.IQ3_S.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.IQ3_S.gguf) | IQ3_S | 3.68GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.IQ3_XS.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.IQ3_XS.gguf) | IQ3_XS | 3.52GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.IQ3_XXS.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.IQ3_XXS.gguf) | IQ3_XXS | 3.27GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.Q2_K.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q2_K.gguf) | Q2_K | 3.18GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.Q2_K_S.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.Q2_K_S.gguf) | Q2_K_S | 2.99GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.IQ2_M.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.IQ2_M.gguf) | IQ2_M | 2.95GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.IQ2_S.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.IQ2_S.gguf) | IQ2_S | 2.76GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.IQ2_XS.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.IQ2_XS.gguf) | IQ2_XS | 2.61GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.IQ2_XXS.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.IQ2_XXS.gguf) | IQ2_XXS | 2.40GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.IQ1_M.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.IQ1_M.gguf) | IQ1_M | 2.16GB | ✅ Available | 🟢 IMatrix | 📦 No
|
||||
| [Llama-Guard-3-8B.IQ1_S.gguf](https://huggingface.co/legraphista/Llama-Guard-3-8B-IMat-GGUF/blob/main/Llama-Guard-3-8B.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/Llama-Guard-3-8B-IMat-GGUF --include "Llama-Guard-3-8B.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/Llama-Guard-3-8B-IMat-GGUF --include "Llama-Guard-3-8B.Q8_0/*" --local-dir ./
|
||||
# see FAQ for merging GGUF's
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Inference
|
||||
|
||||
### Simple chat template
|
||||
```
|
||||
<|begin_of_text|><|start_header_id|>user<|end_header_id|>
|
||||
|
||||
Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.
|
||||
|
||||
<BEGIN UNSAFE CONTENT CATEGORIES>
|
||||
S1: Violent Crimes.
|
||||
S2: Non-Violent Crimes.
|
||||
S3: Sex Crimes.
|
||||
S4: Child Exploitation.
|
||||
S5: Defamation.
|
||||
S6: Specialized Advice.
|
||||
S7: Privacy.
|
||||
S8: Intellectual Property.
|
||||
S9: Indiscriminate Weapons.
|
||||
S10: Hate.
|
||||
S11: Self-Harm.
|
||||
S12: Sexual Content.
|
||||
S13: Elections.
|
||||
S14: Code Interpreter Abuse.
|
||||
<END UNSAFE CONTENT CATEGORIES>
|
||||
|
||||
<BEGIN CONVERSATION>
|
||||
|
||||
User: {user_prompt}
|
||||
|
||||
Agent: {assistant_response}
|
||||
|
||||
User: {next_user_prompt}
|
||||
|
||||
<END CONVERSATION>
|
||||
|
||||
Provide your safety assessment for ONLY THE LAST User message in the above conversation:
|
||||
- First line must read 'safe' or 'unsafe'.
|
||||
- If unsafe, a second line must include a comma-separated list of violated categories.<|eot_id|><|start_header_id|>assistant<|end_header_id|>
|
||||
```
|
||||
|
||||
### Llama.cpp
|
||||
```
|
||||
llama.cpp/main -m Llama-Guard-3-8B.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: `Llama-Guard-3-8B.Q8_0`)
|
||||
3. Run `gguf-split --merge Llama-Guard-3-8B.Q8_0/Llama-Guard-3-8B.Q8_0-00001-of-XXXXX.gguf Llama-Guard-3-8B.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:f60ffcec6dbc3eb23d0fb6c462cc256c691a82373d41e6850610a033c390cd54
|
||||
size 4988176
|
||||
2482
imatrix.dataset
Normal file
2482
imatrix.dataset
Normal file
File diff suppressed because one or more lines are too long
146
imatrix.log
Normal file
146
imatrix.log
Normal file
@@ -0,0 +1,146 @@
|
||||
llama_model_loader: loaded meta data with 28 key-value pairs and 291 tensors from Llama-Guard-3-8B-IMat-GGUF/Llama-Guard-3-8B.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 = Llama Guard 3 8B
|
||||
llama_model_loader: - kv 3: general.basename str = Llama-Guard-3
|
||||
llama_model_loader: - kv 4: general.size_label str = 8B
|
||||
llama_model_loader: - kv 5: general.license str = llama3.1
|
||||
llama_model_loader: - kv 6: general.tags arr[str,6] = ["facebook", "meta", "pytorch", "llam...
|
||||
llama_model_loader: - kv 7: general.languages arr[str,1] = ["en"]
|
||||
llama_model_loader: - kv 8: llama.block_count u32 = 32
|
||||
llama_model_loader: - kv 9: llama.context_length u32 = 131072
|
||||
llama_model_loader: - kv 10: llama.embedding_length u32 = 4096
|
||||
llama_model_loader: - kv 11: llama.feed_forward_length u32 = 14336
|
||||
llama_model_loader: - kv 12: llama.attention.head_count u32 = 32
|
||||
llama_model_loader: - kv 13: llama.attention.head_count_kv u32 = 8
|
||||
llama_model_loader: - kv 14: llama.rope.freq_base f32 = 500000.000000
|
||||
llama_model_loader: - kv 15: llama.attention.layer_norm_rms_epsilon f32 = 0.000010
|
||||
llama_model_loader: - kv 16: general.file_type u32 = 7
|
||||
llama_model_loader: - kv 17: llama.vocab_size u32 = 128256
|
||||
llama_model_loader: - kv 18: llama.rope.dimension_count u32 = 128
|
||||
llama_model_loader: - kv 19: tokenizer.ggml.model str = gpt2
|
||||
llama_model_loader: - kv 20: tokenizer.ggml.pre str = smaug-bpe
|
||||
llama_model_loader: - kv 21: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ...
|
||||
llama_model_loader: - kv 22: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
|
||||
llama_model_loader: - kv 23: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
|
||||
llama_model_loader: - kv 24: tokenizer.ggml.bos_token_id u32 = 128000
|
||||
llama_model_loader: - kv 25: tokenizer.ggml.eos_token_id u32 = 128009
|
||||
llama_model_loader: - kv 26: tokenizer.chat_template str = {% if messages|length % 2 == 0 %}{% s...
|
||||
llama_model_loader: - kv 27: general.quantization_version u32 = 2
|
||||
llama_model_loader: - type f32: 65 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 = Llama Guard 3 8B
|
||||
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 = 7605.33 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 125.056 ms
|
||||
compute_imatrix: computing over 125 chunks with batch_size 512
|
||||
compute_imatrix: 0.66 seconds per pass - ETA 1.37 minutes
|
||||
[1]5.3432,[2]4.1562,[3]3.7953,[4]4.7161,[5]4.7904,[6]4.0998,[7]4.3090,[8]4.7293,[9]4.9040,
|
||||
save_imatrix: stored collected data after 10 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
[10]4.5278,[11]4.9219,[12]5.3672,[13]5.7781,[14]6.1509,[15]6.3996,[16]6.6480,[17]6.8118,[18]6.5864,[19]6.3010,
|
||||
save_imatrix: stored collected data after 20 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
[20]6.2957,[21]6.4152,[22]6.3562,[23]6.6290,[24]6.6010,[25]6.8860,[26]6.8511,[27]6.4964,[28]6.3000,[29]6.3145,
|
||||
save_imatrix: stored collected data after 30 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
[30]6.3011,[31]6.0076,[32]5.7383,[33]5.6159,[34]5.5359,[35]5.5935,[36]5.6462,[37]5.6128,[38]5.6744,[39]5.8076,
|
||||
save_imatrix: stored collected data after 40 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
[40]5.8831,[41]5.7495,[42]5.6111,[43]5.5717,[44]5.5436,[45]5.6278,[46]5.5684,[47]5.6790,[48]5.7627,[49]5.8620,
|
||||
save_imatrix: stored collected data after 50 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
[50]5.8012,[51]5.8768,[52]5.9775,[53]6.0589,[54]6.1242,[55]6.1870,[56]6.2435,[57]6.3130,[58]6.3447,[59]6.3548,
|
||||
save_imatrix: stored collected data after 60 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
[60]6.3314,[61]6.3278,[62]6.3735,[63]6.4200,[64]6.3695,[65]6.3481,[66]6.3653,[67]6.3480,[68]6.3508,[69]6.3479,
|
||||
save_imatrix: stored collected data after 70 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
[70]6.3542,[71]6.3595,[72]6.3685,[73]6.3483,[74]6.3141,[75]6.3217,[76]6.3402,[77]6.3215,[78]6.3276,[79]6.3622,
|
||||
save_imatrix: stored collected data after 80 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
[80]6.3860,[81]6.3747,[82]6.3813,[83]6.4068,[84]6.3337,[85]6.3359,[86]6.3536,[87]6.3687,[88]6.3972,[89]6.4013,
|
||||
save_imatrix: stored collected data after 90 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
[90]6.3511,[91]6.2970,[92]6.2497,[93]6.2038,[94]6.1549,[95]6.1112,[96]6.0844,[97]6.0923,[98]6.1380,[99]6.2109,
|
||||
save_imatrix: stored collected data after 100 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
[100]6.2789,[101]6.3236,[102]6.4281,[103]6.4615,[104]6.4972,[105]6.4421,[106]6.4488,[107]6.4278,[108]6.3883,[109]6.3375,
|
||||
save_imatrix: stored collected data after 110 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
[110]6.3785,[111]6.4288,[112]6.4397,[113]6.4427,[114]6.4710,[115]6.5063,[116]6.5213,[117]6.5361,[118]6.5641,[119]6.5299,
|
||||
save_imatrix: stored collected data after 120 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
[120]6.4958,[121]6.4541,[122]6.4512,[123]6.4408,[124]6.4396,[125]6.4268,
|
||||
save_imatrix: stored collected data after 125 chunks in Llama-Guard-3-8B-IMat-GGUF/imatrix.dat
|
||||
|
||||
llama_print_timings: load time = 2110.40 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 = 69163.99 ms / 64000 tokens ( 1.08 ms per token, 925.34 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 = 71427.12 ms / 64001 tokens
|
||||
|
||||
Final estimate: PPL = 6.4268 +/- 0.08467
|
||||
Reference in New Issue
Block a user