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sha256:d2b6614283badf05d350de7bf6707f311de03562edc1b341801aa45017e30291 +size 5315177600 diff --git a/Qwen2.5-Math-7B-Instruct.i1-Q6_K.gguf b/Qwen2.5-Math-7B-Instruct.i1-Q6_K.gguf new file mode 100644 index 0000000..dc1e7a9 --- /dev/null +++ b/Qwen2.5-Math-7B-Instruct.i1-Q6_K.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0ae3b8860b0f881b35d97ab7e8b1432ae76565ad062a1cdef9ea7701ac253e1d +size 6254199936 diff --git a/README.md b/README.md new file mode 100644 index 0000000..65e4298 --- /dev/null +++ b/README.md @@ -0,0 +1,79 @@ +--- +base_model: Qwen/Qwen2.5-Math-7B-Instruct +language: +- en +library_name: transformers +license: apache-2.0 +license_link: https://huggingface.co/Qwen/Qwen2.5-Math-7B-Instruct/blob/main/LICENSE +quantized_by: mradermacher +tags: +- chat +--- +## About + + + + + + +weighted/imatrix quants of https://huggingface.co/Qwen/Qwen2.5-Math-7B-Instruct + + +static quants are available at https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-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/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-IQ1_S.gguf) | i1-IQ1_S | 2.0 | for the desperate | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-IQ1_M.gguf) | i1-IQ1_M | 2.1 | mostly desperate | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.4 | | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.6 | | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-IQ2_S.gguf) | i1-IQ2_S | 2.7 | | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-IQ2_M.gguf) | i1-IQ2_M | 2.9 | | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q2_K.gguf) | i1-Q2_K | 3.1 | IQ3_XXS probably better | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.2 | lower quality | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.4 | | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.6 | IQ3_XS probably better | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-IQ3_S.gguf) | i1-IQ3_S | 3.6 | beats Q3_K* | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-IQ3_M.gguf) | i1-IQ3_M | 3.7 | | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q3_K_M.gguf) | i1-Q3_K_M | 3.9 | IQ3_S probably better | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.2 | IQ3_M probably better | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.3 | | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q4_0_4_4.gguf) | i1-Q4_0_4_4 | 4.5 | fast on arm, low quality | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q4_0_4_8.gguf) | i1-Q4_0_4_8 | 4.5 | fast on arm+i8mm, low quality | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q4_0_8_8.gguf) | i1-Q4_0_8_8 | 4.5 | fast on arm+sve, low quality | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q4_0.gguf) | i1-Q4_0 | 4.5 | fast, low quality | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.6 | optimal size/speed/quality | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q4_K_M.gguf) | i1-Q4_K_M | 4.8 | fast, recommended | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.4 | | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q5_K_M.gguf) | i1-Q5_K_M | 5.5 | | +| [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Math-7B-Instruct-i1-GGUF/resolve/main/Qwen2.5-Math-7B-Instruct.i1-Q6_K.gguf) | i1-Q6_K | 6.4 | 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. + + diff --git a/imatrix.dat b/imatrix.dat new file mode 100644 index 0000000..1d7ca7b --- /dev/null +++ b/imatrix.dat @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ad31a61bb403dcc51cdc2cf1daa39db989480f7fb3a4dcf42b7d40a13c55427f +size 4536665