From f4e6dac0beb3239849639f425c1ec0ea9814bdb8 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sat, 10 Oct 2026 04:40:17 +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/AutoRefine-Qwen2.5-7B-Instruct-GGUF Source: Original Platform --- .gitattributes | 47 ++++++++++++++ AutoRefine-Qwen2.5-7B-Instruct.IQ4_XS.gguf | 3 + AutoRefine-Qwen2.5-7B-Instruct.Q2_K.gguf | 3 + AutoRefine-Qwen2.5-7B-Instruct.Q3_K_L.gguf | 3 + AutoRefine-Qwen2.5-7B-Instruct.Q3_K_M.gguf | 3 + AutoRefine-Qwen2.5-7B-Instruct.Q3_K_S.gguf | 3 + AutoRefine-Qwen2.5-7B-Instruct.Q4_K_M.gguf | 3 + AutoRefine-Qwen2.5-7B-Instruct.Q4_K_S.gguf | 3 + AutoRefine-Qwen2.5-7B-Instruct.Q5_K_M.gguf | 3 + AutoRefine-Qwen2.5-7B-Instruct.Q5_K_S.gguf | 3 + 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@@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c4b0643c8be70d95fff9f3191f67624714491d6938b1c2d7a36aed4709199f06 +size 15237853760 diff --git a/README.md b/README.md new file mode 100644 index 0000000..b7e3719 --- /dev/null +++ b/README.md @@ -0,0 +1,72 @@ +--- +base_model: yrshi/AutoRefine-Qwen2.5-7B-Instruct +language: +- en +library_name: transformers +license: cc-by-sa-4.0 +mradermacher: + readme_rev: 1 +quantized_by: mradermacher +--- +## About + + + + + + + + + +static quants of https://huggingface.co/yrshi/AutoRefine-Qwen2.5-7B-Instruct + + + +***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#AutoRefine-Qwen2.5-7B-Instruct-GGUF).*** + +weighted/imatrix quants are available at https://huggingface.co/mradermacher/AutoRefine-Qwen2.5-7B-Instruct-i1-GGUF +## 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/AutoRefine-Qwen2.5-7B-Instruct-GGUF/resolve/main/AutoRefine-Qwen2.5-7B-Instruct.Q2_K.gguf) | Q2_K | 3.1 | | +| [GGUF](https://huggingface.co/mradermacher/AutoRefine-Qwen2.5-7B-Instruct-GGUF/resolve/main/AutoRefine-Qwen2.5-7B-Instruct.Q3_K_S.gguf) | Q3_K_S | 3.6 | | +| [GGUF](https://huggingface.co/mradermacher/AutoRefine-Qwen2.5-7B-Instruct-GGUF/resolve/main/AutoRefine-Qwen2.5-7B-Instruct.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality | +| [GGUF](https://huggingface.co/mradermacher/AutoRefine-Qwen2.5-7B-Instruct-GGUF/resolve/main/AutoRefine-Qwen2.5-7B-Instruct.Q3_K_L.gguf) | Q3_K_L | 4.2 | | +| [GGUF](https://huggingface.co/mradermacher/AutoRefine-Qwen2.5-7B-Instruct-GGUF/resolve/main/AutoRefine-Qwen2.5-7B-Instruct.IQ4_XS.gguf) | IQ4_XS | 4.4 | | +| [GGUF](https://huggingface.co/mradermacher/AutoRefine-Qwen2.5-7B-Instruct-GGUF/resolve/main/AutoRefine-Qwen2.5-7B-Instruct.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended | +| [GGUF](https://huggingface.co/mradermacher/AutoRefine-Qwen2.5-7B-Instruct-GGUF/resolve/main/AutoRefine-Qwen2.5-7B-Instruct.Q4_K_M.gguf) | Q4_K_M | 4.8 | fast, recommended | +| [GGUF](https://huggingface.co/mradermacher/AutoRefine-Qwen2.5-7B-Instruct-GGUF/resolve/main/AutoRefine-Qwen2.5-7B-Instruct.Q5_K_S.gguf) | Q5_K_S | 5.4 | | +| [GGUF](https://huggingface.co/mradermacher/AutoRefine-Qwen2.5-7B-Instruct-GGUF/resolve/main/AutoRefine-Qwen2.5-7B-Instruct.Q5_K_M.gguf) | Q5_K_M | 5.5 | | +| [GGUF](https://huggingface.co/mradermacher/AutoRefine-Qwen2.5-7B-Instruct-GGUF/resolve/main/AutoRefine-Qwen2.5-7B-Instruct.Q6_K.gguf) | Q6_K | 6.4 | very good quality | +| [GGUF](https://huggingface.co/mradermacher/AutoRefine-Qwen2.5-7B-Instruct-GGUF/resolve/main/AutoRefine-Qwen2.5-7B-Instruct.Q8_0.gguf) | Q8_0 | 8.2 | fast, best quality | +| [GGUF](https://huggingface.co/mradermacher/AutoRefine-Qwen2.5-7B-Instruct-GGUF/resolve/main/AutoRefine-Qwen2.5-7B-Instruct.f16.gguf) | f16 | 15.3 | 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. + +