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sha256:09fea7d0968dd6ae8f219822db2c19d10c968c8fc5bf030718d49c8323f2778f +size 622729824 diff --git a/DeepBrainz-R1-0.6B-v2.imatrix.gguf b/DeepBrainz-R1-0.6B-v2.imatrix.gguf new file mode 100644 index 0000000..d924608 --- /dev/null +++ b/DeepBrainz-R1-0.6B-v2.imatrix.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4d9ab89ed02b5f6402aec162a058882f25a0ae6146e4126f65030665508cd2d4 +size 1177056 diff --git a/README.md b/README.md new file mode 100644 index 0000000..6789cf3 --- /dev/null +++ b/README.md @@ -0,0 +1,92 @@ +--- +base_model: DeepBrainz/DeepBrainz-R1-0.6B-v2 +language: +- en +library_name: transformers +license: apache-2.0 +mradermacher: + readme_rev: 1 +quantized_by: mradermacher +tags: +- deepbrainz +- reasoning +- mathematics +- code +- enterprise +- 0.6b +--- +## About + + + + + + + + + +weighted/imatrix quants of https://huggingface.co/DeepBrainz/DeepBrainz-R1-0.6B-v2 + + + +***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#DeepBrainz-R1-0.6B-v2-i1-GGUF).*** + +static quants are available at https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-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/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-IQ1_S.gguf) | i1-IQ1_S | 0.4 | for the desperate | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-IQ1_M.gguf) | i1-IQ1_M | 0.4 | mostly desperate | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 0.4 | | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-IQ2_XS.gguf) | i1-IQ2_XS | 0.4 | | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-IQ2_S.gguf) | i1-IQ2_S | 0.4 | | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-Q2_K_S.gguf) | i1-Q2_K_S | 0.4 | very low quality | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-IQ2_M.gguf) | i1-IQ2_M | 0.4 | | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 0.4 | lower quality | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-Q2_K.gguf) | i1-Q2_K | 0.4 | IQ3_XXS probably better | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-IQ3_XS.gguf) | i1-IQ3_XS | 0.5 | | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-IQ3_S.gguf) | i1-IQ3_S | 0.5 | beats Q3_K* | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-Q3_K_S.gguf) | i1-Q3_K_S | 0.5 | IQ3_XS probably better | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-IQ3_M.gguf) | i1-IQ3_M | 0.5 | | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-Q3_K_M.gguf) | i1-Q3_K_M | 0.5 | IQ3_S probably better | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-Q3_K_L.gguf) | i1-Q3_K_L | 0.5 | IQ3_M probably better | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-IQ4_XS.gguf) | i1-IQ4_XS | 0.6 | | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-IQ4_NL.gguf) | i1-IQ4_NL | 0.6 | prefer IQ4_XS | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-Q4_0.gguf) | i1-Q4_0 | 0.6 | fast, low quality | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-Q4_K_S.gguf) | i1-Q4_K_S | 0.6 | optimal size/speed/quality | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-Q4_K_M.gguf) | i1-Q4_K_M | 0.6 | fast, recommended | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-Q4_1.gguf) | i1-Q4_1 | 0.6 | | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-Q5_K_S.gguf) | i1-Q5_K_S | 0.6 | | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-Q5_K_M.gguf) | i1-Q5_K_M | 0.7 | | +| [GGUF](https://huggingface.co/mradermacher/DeepBrainz-R1-0.6B-v2-i1-GGUF/resolve/main/DeepBrainz-R1-0.6B-v2.i1-Q6_K.gguf) | i1-Q6_K | 0.7 | 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. + +