--- 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. 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Fail to appropriately disclose to\ \ end users any known dangers of your AI system\nPlease report any violation of\ \ this Policy, software \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 | IQ4_NL | - | ⏳ Processing | 🟢 IMatrix | - | Llama-Guard-3-8B.IQ4_XS | IQ4_XS | - | ⏳ Processing | 🟢 IMatrix | - | [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 | IQ3_M | - | ⏳ Processing | 🟢 IMatrix | - | Llama-Guard-3-8B.IQ3_S | IQ3_S | - | ⏳ Processing | 🟢 IMatrix | - | Llama-Guard-3-8B.IQ3_XS | IQ3_XS | - | ⏳ Processing | 🟢 IMatrix | - | Llama-Guard-3-8B.IQ3_XXS | IQ3_XXS | - | ⏳ Processing | 🟢 IMatrix | - | [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 | Q2_K_S | - | ⏳ Processing | 🟢 IMatrix | - | Llama-Guard-3-8B.IQ2_M | IQ2_M | - | ⏳ Processing | 🟢 IMatrix | - | Llama-Guard-3-8B.IQ2_S | IQ2_S | - | ⏳ Processing | 🟢 IMatrix | - | Llama-Guard-3-8B.IQ2_XS | IQ2_XS | - | ⏳ Processing | 🟢 IMatrix | - | Llama-Guard-3-8B.IQ2_XXS | IQ2_XXS | - | ⏳ Processing | 🟢 IMatrix | - | Llama-Guard-3-8B.IQ1_M | IQ1_M | - | ⏳ Processing | 🟢 IMatrix | - | Llama-Guard-3-8B.IQ1_S | IQ1_S | - | ⏳ Processing | 🟢 IMatrix | - ## 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. 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. User: {user_prompt} Agent: {assistant_response} User: {next_user_prompt} 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)!