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---
base_model: meta-llama/Llama-3.2-1B-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_prompt: "### LLAMA 3.2 COMMUNITY LICENSE AGREEMENT\n\nLlama 3.2 Version\
\ Release Date: September 25, 2024\n\n\u201CAgreement\u201D means the terms and\
\ conditions for use, reproduction, distribution and modification of the Llama\
\ Materials set forth herein.\n\n\u201CDocumentation\u201D means the specifications,\
\ manuals and documentation accompanying Llama 3.2 distributed by Meta at https://llama.meta.com/doc/overview.\n\
\n\u201CLicensee\u201D or \u201Cyou\u201D means you, or your employer or any other\
\ person or entity (if you are entering into this Agreement on such person or entity\u2019\
s behalf), of the age required under applicable laws, rules or regulations to provide\
\ legal consent and that has legal authority to bind your employer or such other\
\ person or entity if you are entering in this Agreement on their behalf.\n\n\u201C\
Llama 3.2\u201D 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://www.llama.com/llama-downloads.\n\
\n\u201CLlama Materials\u201D means, collectively, Meta\u2019s proprietary Llama\
\ 3.2 and Documentation (and any portion thereof) made available under this Agreement.\n\
\n\u201CMeta\u201D or \u201Cwe\u201D 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\nBy clicking \u201CI Accept\u201D below or by using\
\ or distributing any portion or element of the Llama Materials, you agree to be\
\ bound by this Agreement.\n\n1. License Rights and Redistribution.\na. Grant of\
\ Rights. You are granted a non-exclusive, worldwide, non-transferable and royalty-free\
\ limited license under Meta\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. \nb. Redistribution\
\ and Use. \ni. If you distribute or make available the Llama Materials (or any\
\ derivative works thereof), or a product or service (including another AI model)\
\ that contains any of them, you shall (A) provide a copy of this Agreement with\
\ any such Llama Materials; and (B) prominently display \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 3.2 is licensed under the Llama 3.2 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://www.llama.com/llama3_2/use-policy), which is hereby incorporated\
\ by reference into this Agreement.\n \n2. Additional Commercial Terms. If, on\
\ the Llama 3.2 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.\n4. Limitation of Liability. IN NO EVENT\
\ WILL META OR ITS AFFILIATES BE LIABLE UNDER ANY THEORY OF LIABILITY, WHETHER\
\ IN CONTRACT, TORT, NEGLIGENCE, PRODUCTS LIABILITY, OR OTHERWISE, ARISING OUT OF\
\ THIS AGREEMENT, FOR ANY LOST PROFITS OR ANY INDIRECT, SPECIAL, CONSEQUENTIAL,\
\ INCIDENTAL, EXEMPLARY OR PUNITIVE DAMAGES, EVEN IF META OR ITS AFFILIATES HAVE\
\ BEEN ADVISED OF THE POSSIBILITY OF ANY OF THE FOREGOING.\n5. Intellectual Property.\n\
a. No trademark licenses are granted under this Agreement, and in connection with\
\ the Llama Materials, neither Meta nor Licensee may use any name or mark owned\
\ by or associated with the other or any of its affiliates, except as required\
\ for reasonable and customary use in describing and redistributing the Llama Materials\
\ or as set forth in this Section 5(a). Meta hereby grants you a license to use\
\ \u201CLlama\u201D (the \u201CMark\u201D) solely as required to comply with the\
\ last sentence of Section 1.b.i. You will comply with Meta\u2019s 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 3.2 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 3.2 Acceptable Use Policy\n\
Meta is committed to promoting safe and fair use of its tools and features, including\
\ Llama 3.2. If you access or use Llama 3.2, you agree to this Acceptable Use Policy\
\ (\u201C**Policy**\u201D). The most recent copy of this policy can be found at\
\ [https://www.llama.com/llama3_2/use-policy](https://www.llama.com/llama3_2/use-policy).\n\
#### Prohibited Uses\nWe want everyone to use Llama 3.2 safely and responsibly.\
\ You agree you will not use, or allow others to use, Llama 3.2 to:\n1. 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 1. Engage in, promote, incite, or facilitate the\
\ harassment, abuse, threatening, or bullying of individuals or groups of individuals\n\
\ 2. 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 3.\
\ Engage in the unauthorized or unlicensed practice of any profession including,\
\ but not limited to, financial, legal, medical/health, or related professional\
\ practices\n 4. Collect, process, disclose, generate, or infer private or sensitive\
\ information about individuals, including information about individuals\u2019 identity,\
\ health, or demographic information, unless you have obtained the right to do so\
\ in accordance with applicable law\n 5. 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 6. 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\n 7. Engage in any action, or\
\ facilitate any action, to intentionally circumvent or remove usage restrictions\
\ or other safety measures, or to enable functionality disabled by Meta\_\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\
\ 3.2 related to the following:\n 8. 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 or to the U.S. Biological Weapons Anti-Terrorism Act of 1989\
\ or the Chemical Weapons Convention Implementation Act of 1997\n 9. Guns and\
\ illegal weapons (including weapon development)\n 10. Illegal drugs and regulated/controlled\
\ substances\n 11. Operation of critical infrastructure, transportation technologies,\
\ or heavy machinery\n 12. Self-harm or harm to others, including suicide, cutting,\
\ and eating disorders\n 13. 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 3.2 related to the following:\n 14.\
\ Generating, promoting, or furthering fraud or the creation or promotion of disinformation\n\
\ 15. Generating, promoting, or furthering defamatory content, including the\
\ creation of defamatory statements, images, or other content\n 16. Generating,\
\ promoting, or further distributing spam\n 17. Impersonating another individual\
\ without consent, authorization, or legal right\n 18. Representing that the\
\ use of Llama 3.2 or outputs are human-generated\n 19. 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 5. Interact with third party tools, models, or software designed\
\ to generate unlawful content or engage in unlawful or harmful conduct and/or represent\
\ that the outputs of such tools, models, or software are associated with Meta or\
\ Llama 3.2\n\nWith respect to any multimodal models included in Llama 3.2, the\
\ rights granted under Section 1(a) of the Llama 3.2 Community License Agreement\
\ are not being granted to you if you are an individual domiciled in, or a company\
\ with a principal place of business in, the European Union. This restriction does\
\ not apply to end users of a product or service that incorporates any such multimodal\
\ models.\n\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\n* Reporting issues with the model: [https://github.com/meta-llama/llama-models/issues](https://l.workplace.com/l.php?u=https%3A%2F%2Fgithub.com%2Fmeta-llama%2Fllama-models%2Fissues&h=AT0qV8W9BFT6NwihiOHRuKYQM_UnkzN_NmHMy91OT55gkLpgi4kQupHUl0ssR4dQsIQ8n3tfd0vtkobvsEvt1l4Ic6GXI2EeuHV8N08OG2WnbAmm0FL4ObkazC6G_256vN0lN9DsykCvCqGZ)\n\
* Reporting risky content generated by the model: [developers.facebook.com/llama_output_feedback](http://developers.facebook.com/llama_output_feedback)\n\
* Reporting bugs and security concerns: [facebook.com/whitehat/info](http://facebook.com/whitehat/info)\n\
* Reporting violations of the Acceptable Use Policy or unlicensed uses of Llama\
\ 3.2: LlamaUseReport@meta.com"
inference: false
language:
- en
- de
- fr
- it
- pt
- hi
- es
- th
library_name: gguf
license: llama3.2
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-3.2-1B-Instruct-IMat-GGUF
_Llama.cpp imatrix quantization of meta-llama/Llama-3.2-1B-Instruct_
Original Model: [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct)
Original dtype: `BF16` (`bfloat16`)
Quantized by: llama.cpp [b3825](https://github.com/ggerganov/llama.cpp/releases/tag/b3825)
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/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/imatrix.dat)
### Common Quants
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
| -------- | ---------- | --------- | ------ | ------------ | -------- |
| [Llama-3.2-1B-Instruct.Q8_0.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q8_0.gguf) | Q8_0 | 1.32GB | ✅ Available | ⚪ Static | 📦 No
| [Llama-3.2-1B-Instruct.Q6_K.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q6_K.gguf) | Q6_K | 1.02GB | ✅ Available | ⚪ Static | 📦 No
| [Llama-3.2-1B-Instruct.Q4_K.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q4_K.gguf) | Q4_K | 807.69MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.Q3_K.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q3_K.gguf) | Q3_K | 690.84MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.Q2_K.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q2_K.gguf) | Q2_K | 580.87MB | ✅ Available | 🟢 IMatrix | 📦 No
### All Quants
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
| -------- | ---------- | --------- | ------ | ------------ | -------- |
| [Llama-3.2-1B-Instruct.BF16.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.BF16.gguf) | BF16 | 2.48GB | ✅ Available | ⚪ Static | 📦 No
| [Llama-3.2-1B-Instruct.FP16.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.FP16.gguf) | F16 | 2.48GB | ✅ Available | ⚪ Static | 📦 No
| [Llama-3.2-1B-Instruct.Q8_0.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q8_0.gguf) | Q8_0 | 1.32GB | ✅ Available | ⚪ Static | 📦 No
| [Llama-3.2-1B-Instruct.Q6_K.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q6_K.gguf) | Q6_K | 1.02GB | ✅ Available | ⚪ Static | 📦 No
| [Llama-3.2-1B-Instruct.Q5_K.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q5_K.gguf) | Q5_K | 911.50MB | ✅ Available | ⚪ Static | 📦 No
| [Llama-3.2-1B-Instruct.Q5_K_S.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q5_K_S.gguf) | Q5_K_S | 892.56MB | ✅ Available | ⚪ Static | 📦 No
| [Llama-3.2-1B-Instruct.Q4_K.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q4_K.gguf) | Q4_K | 807.69MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.Q4_K_S.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q4_K_S.gguf) | Q4_K_S | 775.65MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.IQ4_NL.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.IQ4_NL.gguf) | IQ4_NL | 773.03MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.IQ4_XS.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.IQ4_XS.gguf) | IQ4_XS | 743.14MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.Q3_K.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q3_K.gguf) | Q3_K | 690.84MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.Q3_K_L.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q3_K_L.gguf) | Q3_K_L | 732.52MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.Q3_K_S.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q3_K_S.gguf) | Q3_K_S | 641.69MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.IQ3_M.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.IQ3_M.gguf) | IQ3_M | 657.29MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.IQ3_S.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.IQ3_S.gguf) | IQ3_S | 643.92MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.IQ3_XS.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.IQ3_XS.gguf) | IQ3_XS | 621.11MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.IQ3_XXS.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.IQ3_XXS.gguf) | IQ3_XXS | 562.11MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.Q2_K.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q2_K.gguf) | Q2_K | 580.87MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.Q2_K_S.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.Q2_K_S.gguf) | Q2_K_S | 554.66MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.IQ2_M.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.IQ2_M.gguf) | IQ2_M | 515.45MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.IQ2_S.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.IQ2_S.gguf) | IQ2_S | 488.71MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.IQ2_XS.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.IQ2_XS.gguf) | IQ2_XS | 475.87MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.IQ2_XXS.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.IQ2_XXS.gguf) | IQ2_XXS | 447.03MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.IQ1_M.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.IQ1_M.gguf) | IQ1_M | 413.61MB | ✅ Available | 🟢 IMatrix | 📦 No
| [Llama-3.2-1B-Instruct.IQ1_S.gguf](https://huggingface.co/legraphista/Llama-3.2-1B-Instruct-IMat-GGUF/blob/main/Llama-3.2-1B-Instruct.IQ1_S.gguf) | IQ1_S | 393.55MB | ✅ 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-3.2-1B-Instruct-IMat-GGUF --include "Llama-3.2-1B-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/Llama-3.2-1B-Instruct-IMat-GGUF --include "Llama-3.2-1B-Instruct.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's
```
---
## Inference
### Simple chat template
```
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
Cutting Knowledge Date: December 2023
Today Date: 26 Jul 2024
<|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|>
```
### Chat template with system prompt
```
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
Cutting Knowledge Date: December 2023
Today Date: 26 Jul 2024
{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|>
```
### Llama.cpp
```
llama.cpp/main -m Llama-3.2-1B-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: `Llama-3.2-1B-Instruct.Q8_0`)
3. Run `gguf-split --merge Llama-3.2-1B-Instruct.Q8_0/Llama-3.2-1B-Instruct.Q8_0-00001-of-XXXXX.gguf Llama-3.2-1B-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)!

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build: 3825 (1e436302) with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
llama_model_loader: loaded meta data with 31 key-value pairs and 147 tensors from Llama-3.2-1B-Instruct-IMat-GGUF/Llama-3.2-1B-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 = Llama 3.2 1B Instruct
llama_model_loader: - kv 3: general.finetune str = Instruct
llama_model_loader: - kv 4: general.basename str = Llama-3.2
llama_model_loader: - kv 5: general.size_label str = 1B
llama_model_loader: - kv 6: general.license str = llama3.2
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 = 16
llama_model_loader: - kv 10: llama.context_length u32 = 131072
llama_model_loader: - kv 11: llama.embedding_length u32 = 2048
llama_model_loader: - kv 12: llama.feed_forward_length u32 = 8192
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: llama.attention.key_length u32 = 64
llama_model_loader: - kv 18: llama.attention.value_length u32 = 64
llama_model_loader: - kv 19: general.file_type u32 = 7
llama_model_loader: - kv 20: llama.vocab_size u32 = 128256
llama_model_loader: - kv 21: llama.rope.dimension_count u32 = 64
llama_model_loader: - kv 22: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 23: tokenizer.ggml.pre str = llama-bpe
llama_model_loader: - kv 24: tokenizer.ggml.tokens arr[str,128256] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 25: tokenizer.ggml.token_type arr[i32,128256] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 26: tokenizer.ggml.merges arr[str,280147] = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv 27: tokenizer.ggml.bos_token_id u32 = 128000
llama_model_loader: - kv 28: tokenizer.ggml.eos_token_id u32 = 128009
llama_model_loader: - kv 29: tokenizer.chat_template str = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - kv 30: general.quantization_version u32 = 2
llama_model_loader: - type f32: 34 tensors
llama_model_loader: - type q8_0: 113 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 = 2048
llm_load_print_meta: n_layer = 16
llm_load_print_meta: n_head = 32
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_rot = 64
llm_load_print_meta: n_swa = 0
llm_load_print_meta: n_embd_head_k = 64
llm_load_print_meta: n_embd_head_v = 64
llm_load_print_meta: n_gqa = 4
llm_load_print_meta: n_embd_k_gqa = 512
llm_load_print_meta: n_embd_v_gqa = 512
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 = 8192
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: ssm_dt_b_c_rms = 0
llm_load_print_meta: model type = ?B
llm_load_print_meta: model ftype = Q8_0
llm_load_print_meta: model params = 1.24 B
llm_load_print_meta: model size = 1.22 GiB (8.50 BPW)
llm_load_print_meta: general.name = Llama 3.2 1B 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: EOM token = 128008 '<|eom_id|>'
llm_load_print_meta: EOG token = 128008 '<|eom_id|>'
llm_load_print_meta: EOG 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 = 0.14 MiB
llm_load_tensors: offloading 16 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 17/17 layers to GPU
llm_load_tensors: CPU buffer size = 266.16 MiB
llm_load_tensors: CUDA0 buffer size = 1252.42 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 = 16.00 MiB
llama_new_context_with_model: KV self size = 16.00 MiB, K (f16): 8.00 MiB, V (f16): 8.00 MiB
llama_new_context_with_model: CUDA_Host output buffer size = 0.49 MiB
llama_new_context_with_model: CUDA0 compute buffer size = 254.50 MiB
llama_new_context_with_model: CUDA_Host compute buffer size = 5.01 MiB
llama_new_context_with_model: graph nodes = 518
llama_new_context_with_model: graph splits = 2
system_info: n_threads = 25 (n_threads_batch = 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 | RISCV_VECT = 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 41.228 ms
compute_imatrix: computing over 125 chunks with batch_size 512
compute_imatrix: 0.27 seconds per pass - ETA 0.55 minutes
[1]10.1003,[2]8.7720,[3]7.6214,[4]9.5709,[5]9.9748,[6]8.1803,[7]8.9931,[8]9.8189,[9]9.8290,[10]8.8016,[11]9.5176,[12]10.4471,[13]11.0957,[14]11.5884,[15]11.9080,[16]12.2895,[17]12.5080,[18]12.0233,[19]11.3547,[20]11.3911,[21]11.7520,[22]11.6329,[23]12.1215,[24]12.1673,[25]12.5908,[26]12.6425,[27]12.8542,[28]13.3951,[29]13.4406,[30]13.4958,[31]12.6603,[32]11.9421,[33]11.5444,[34]11.1900,[35]11.4356,[36]11.7923,[37]11.7055,[38]11.7950,[39]12.0074,[40]12.1217,[41]12.5260,[42]12.9512,[43]13.4504,[44]13.7702,[45]14.1608,[46]13.8227,[47]14.0141,[48]14.1086,[49]14.2237,[50]13.9614,[51]14.0995,[52]14.3164,[53]14.4866,[54]14.6511,[55]14.7375,[56]14.7230,[57]14.7250,[58]14.6895,[59]14.7109,[60]14.5806,[61]14.4905,[62]14.5499,[63]14.5756,[64]14.4582,[65]14.4160,[66]14.4073,[67]14.3236,[68]14.2669,[69]14.2115,[70]14.1506,[71]14.0868,[72]14.0321,[73]13.9478,[74]13.8268,[75]13.8096,[76]13.8170,[77]13.7423,[78]13.7053,[79]13.7641,[80]13.7904,[81]13.7380,[82]13.7433,[83]13.7881,[84]13.5757,[85]13.6192,[86]13.6431,[87]13.6291,[88]13.6536,[89]13.6300,[90]13.4896,[91]13.3255,[92]13.1715,[93]13.0364,[94]12.9000,[95]12.7725,[96]12.6925,[97]12.6859,[98]12.7142,[99]12.8512,[100]12.9701,[101]13.0520,[102]13.2456,[103]13.2737,[104]13.3239,[105]13.1657,[106]13.1447,[107]13.0611,[108]12.9922,[109]12.9131,[110]12.9894,[111]13.0774,[112]13.0733,[113]13.0816,[114]13.1270,[115]13.1905,[116]13.1885,[117]13.1985,[118]13.2109,[119]13.1053,[120]13.2112,[121]13.3304,[122]13.3987,[123]13.5091,[124]13.6236,[125]13.7181,
Final estimate: PPL = 13.7181 +/- 0.21967
llama_perf_context_print: load time = 892.41 ms
llama_perf_context_print: prompt eval time = 18897.20 ms / 64000 tokens ( 0.30 ms per token, 3386.75 tokens per second)
llama_perf_context_print: eval time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second)
llama_perf_context_print: total time = 20329.73 ms / 64001 tokens