From b8b2fd8db7f8d71c6179da7e7a768b4d9d61cfb7 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sun, 31 May 2026 10:20:15 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF Source: Original Platform --- .gitattributes | 47 +++++++++++ Pythonified-Llama-3.2-3B-Instruct.IQ4_XS.gguf | 3 + Pythonified-Llama-3.2-3B-Instruct.Q2_K.gguf | 3 + Pythonified-Llama-3.2-3B-Instruct.Q3_K_L.gguf | 3 + Pythonified-Llama-3.2-3B-Instruct.Q3_K_M.gguf | 3 + Pythonified-Llama-3.2-3B-Instruct.Q3_K_S.gguf | 3 + Pythonified-Llama-3.2-3B-Instruct.Q4_K_M.gguf | 3 + Pythonified-Llama-3.2-3B-Instruct.Q4_K_S.gguf | 3 + Pythonified-Llama-3.2-3B-Instruct.Q5_K_M.gguf | 3 + Pythonified-Llama-3.2-3B-Instruct.Q5_K_S.gguf | 3 + 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this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion. +## Usage + +If you are unsure how to use GGUF files, refer to one of [TheBloke's +READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for +more details, including on how to concatenate multi-part files. + +## Provided Quants + +(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) + +| Link | Type | Size/GB | Notes | +|:-----|:-----|--------:|:------| +| [GGUF](https://huggingface.co/mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct.Q2_K.gguf) | Q2_K | 1.5 | | +| [GGUF](https://huggingface.co/mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct.Q3_K_S.gguf) | Q3_K_S | 1.6 | | +| [GGUF](https://huggingface.co/mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct.Q3_K_M.gguf) | Q3_K_M | 1.8 | lower quality | +| [GGUF](https://huggingface.co/mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct.Q3_K_L.gguf) | Q3_K_L | 1.9 | | +| [GGUF](https://huggingface.co/mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct.IQ4_XS.gguf) | IQ4_XS | 1.9 | | +| [GGUF](https://huggingface.co/mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct.Q4_K_S.gguf) | Q4_K_S | 2.0 | fast, recommended | +| [GGUF](https://huggingface.co/mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct.Q4_K_M.gguf) | Q4_K_M | 2.1 | fast, recommended | +| [GGUF](https://huggingface.co/mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct.Q5_K_S.gguf) | Q5_K_S | 2.4 | | +| [GGUF](https://huggingface.co/mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct.Q5_K_M.gguf) | Q5_K_M | 2.4 | | +| [GGUF](https://huggingface.co/mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct.Q6_K.gguf) | Q6_K | 2.7 | very good quality | +| [GGUF](https://huggingface.co/mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct.Q8_0.gguf) | Q8_0 | 3.5 | fast, best quality | +| [GGUF](https://huggingface.co/mradermacher/Pythonified-Llama-3.2-3B-Instruct-GGUF/resolve/main/Pythonified-Llama-3.2-3B-Instruct.f16.gguf) | f16 | 6.5 | 16 bpw, overkill | + +Here is a handy graph by ikawrakow comparing some lower-quality quant +types (lower is better): + +![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) + +And here are Artefact2's thoughts on the matter: +https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 + +## FAQ / Model Request + +See https://huggingface.co/mradermacher/model_requests for some answers to +questions you might have and/or if you want some other model quantized. + +## Thanks + +I thank my company, [nethype GmbH](https://www.nethype.de/), for letting +me use its servers and providing upgrades to my workstation to enable +this work in my free time. + +