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+size 19345940576 diff --git a/README.md b/README.md new file mode 100644 index 0000000..515be93 --- /dev/null +++ b/README.md @@ -0,0 +1,81 @@ +--- +base_model: yentinglin/Mistral-Small-24B-Instruct-2501-reasoning +datasets: +- open-r1/OpenR1-Math-220k +- yentinglin/s1K-1.1-trl-format +- simplescaling/s1K-1.1 +language: +- en +library_name: transformers +license: apache-2.0 +quantized_by: mradermacher +tags: +- reasoning +--- +## About + + + + + + +weighted/imatrix quants of https://huggingface.co/yentinglin/Mistral-Small-24B-Instruct-2501-reasoning + + +static quants are available at https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-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/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-IQ1_S.gguf) | i1-IQ1_S | 5.4 | for the desperate | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-IQ1_M.gguf) | i1-IQ1_M | 5.9 | mostly desperate | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 6.6 | | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-IQ2_XS.gguf) | i1-IQ2_XS | 7.3 | | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-IQ2_S.gguf) | i1-IQ2_S | 7.6 | | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-IQ2_M.gguf) | i1-IQ2_M | 8.2 | | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-Q2_K_S.gguf) | i1-Q2_K_S | 8.4 | very low quality | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-Q2_K.gguf) | i1-Q2_K | 9.0 | IQ3_XXS probably better | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 9.4 | lower quality | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-IQ3_XS.gguf) | i1-IQ3_XS | 10.0 | | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-Q3_K_S.gguf) | i1-Q3_K_S | 10.5 | IQ3_XS probably better | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-IQ3_S.gguf) | i1-IQ3_S | 10.5 | beats Q3_K* | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-IQ3_M.gguf) | i1-IQ3_M | 10.8 | | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-Q3_K_M.gguf) | i1-Q3_K_M | 11.6 | IQ3_S probably better | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-Q3_K_L.gguf) | i1-Q3_K_L | 12.5 | IQ3_M probably better | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-IQ4_XS.gguf) | i1-IQ4_XS | 12.9 | | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-Q4_0.gguf) | i1-Q4_0 | 13.6 | fast, low quality | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-Q4_K_S.gguf) | i1-Q4_K_S | 13.6 | optimal size/speed/quality | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-Q4_K_M.gguf) | i1-Q4_K_M | 14.4 | fast, recommended | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-Q4_1.gguf) | i1-Q4_1 | 15.0 | | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-Q5_K_S.gguf) | i1-Q5_K_S | 16.4 | | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-Q5_K_M.gguf) | i1-Q5_K_M | 16.9 | | +| [GGUF](https://huggingface.co/mradermacher/Mistral-Small-24B-Instruct-2501-reasoning-i1-GGUF/resolve/main/Mistral-Small-24B-Instruct-2501-reasoning.i1-Q6_K.gguf) | i1-Q6_K | 19.4 | practically like static Q6_K | + +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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to. + +