From 56e48692abed3bd1f01496a9a4897bda792fae4d Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Fri, 16 Oct 2026 10:14:25 +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/EVA-Qwen2.5-1.5B-v0.0-GGUF Source: Original Platform --- .gitattributes | 47 +++++++++++++++++++ EVA-Qwen2.5-1.5B-v0.0.IQ4_XS.gguf | 3 ++ EVA-Qwen2.5-1.5B-v0.0.Q2_K.gguf | 3 ++ EVA-Qwen2.5-1.5B-v0.0.Q3_K_L.gguf | 3 ++ EVA-Qwen2.5-1.5B-v0.0.Q3_K_M.gguf | 3 ++ EVA-Qwen2.5-1.5B-v0.0.Q3_K_S.gguf | 3 ++ EVA-Qwen2.5-1.5B-v0.0.Q4_K_M.gguf | 3 ++ EVA-Qwen2.5-1.5B-v0.0.Q4_K_S.gguf | 3 ++ EVA-Qwen2.5-1.5B-v0.0.Q5_K_M.gguf | 3 ++ EVA-Qwen2.5-1.5B-v0.0.Q5_K_S.gguf | 3 ++ EVA-Qwen2.5-1.5B-v0.0.Q6_K.gguf | 3 ++ EVA-Qwen2.5-1.5B-v0.0.Q8_0.gguf | 3 ++ EVA-Qwen2.5-1.5B-v0.0.f16.gguf | 3 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cognitivecomputations/dolphin-2.9.3 +language: +- en +library_name: transformers +license: apache-2.0 +quantized_by: mradermacher +tags: +- generated_from_trainer +--- +## About + + + + + + +static quants of https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-1.5B-v0.0 + + +weighted/imatrix quants seem not to be available (by me) at 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/EVA-Qwen2.5-1.5B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-1.5B-v0.0.Q2_K.gguf) | Q2_K | 0.8 | | +| [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-1.5B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-1.5B-v0.0.Q3_K_S.gguf) | Q3_K_S | 0.9 | | +| [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-1.5B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-1.5B-v0.0.Q3_K_M.gguf) | Q3_K_M | 0.9 | lower quality | +| [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-1.5B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-1.5B-v0.0.Q3_K_L.gguf) | Q3_K_L | 1.0 | | +| [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-1.5B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-1.5B-v0.0.IQ4_XS.gguf) | IQ4_XS | 1.0 | | +| [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-1.5B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-1.5B-v0.0.Q4_K_S.gguf) | Q4_K_S | 1.0 | fast, recommended | +| [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-1.5B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-1.5B-v0.0.Q4_K_M.gguf) | Q4_K_M | 1.1 | fast, recommended | +| [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-1.5B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-1.5B-v0.0.Q5_K_S.gguf) | Q5_K_S | 1.2 | | +| [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-1.5B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-1.5B-v0.0.Q5_K_M.gguf) | Q5_K_M | 1.2 | | +| [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-1.5B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-1.5B-v0.0.Q6_K.gguf) | Q6_K | 1.4 | very good quality | +| [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-1.5B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-1.5B-v0.0.Q8_0.gguf) | Q8_0 | 1.7 | fast, best quality | +| [GGUF](https://huggingface.co/mradermacher/EVA-Qwen2.5-1.5B-v0.0-GGUF/resolve/main/EVA-Qwen2.5-1.5B-v0.0.f16.gguf) | f16 | 3.2 | 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. + +