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For a convenient overview and download list, visit our model page for this model.
Fuente del modelo
Descripción de la fuente
weighted/imatrix quants of https://huggingface.co/aryyanthakrr/Kepler-Reasoning-7B
For a convenient overview and download list, visit our model page for this model.
static quants are available at
Fuentes
1 fuenteVerificado 6 ago
Artefactos del modelo
25 artefactosExtractos de fuentes
3 extractosIf you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
| Link | Type | Size/GB | Notes |
|---|---|---|---|
| GGUF | imatrix | 0.1 | imatrix file (for creating your own quants) |
| GGUF | i1-IQ1_S | 2.0 | for the desperate |
| GGUF | i1-IQ1_M | 2.1 | mostly desperate |
| GGUF | i1-IQ2_XXS | 2.4 | |
Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
image.png
And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.
I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to @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.
Kepler-Reasoning-7B.i1-IQ2_XS.gguf
gguf · 2,30 GB · SHA-256 d504282bcfc7…762e · Hugging Face
DescargarKepler-Reasoning-7B.i1-IQ2_XXS.gguf
gguf · 2,12 GB · SHA-256 fbb473b5e345…ee9a · Hugging Face
DescargarKepler-Reasoning-7B.i1-IQ3_XS.gguf
gguf · 3,11 GB · SHA-256 112f3f8301c9…8e3a · Hugging Face
DescargarKepler-Reasoning-7B.i1-IQ3_XXS.gguf
gguf · 2,90 GB · SHA-256 b3295e3c90a8…d93c · Hugging Face
DescargarKepler-Reasoning-7B.i1-IQ4_NL.gguf
gguf · 4,13 GB · SHA-256 416ff89aa84d…b6e3 · Hugging Face
DescargarKepler-Reasoning-7B.i1-IQ4_XS.gguf
gguf · 3,93 GB · SHA-256 090fa2160b61…6802 · Hugging Face
DescargarKepler-Reasoning-7B.i1-Q2_K_S.gguf
gguf · 2,64 GB · SHA-256 efd9d8dcaccd…89a1 · Hugging Face
DescargarKepler-Reasoning-7B.i1-Q3_K_L.gguf
gguf · 3,81 GB · SHA-256 ad797a79559f…089f · Hugging Face
DescargarKepler-Reasoning-7B.i1-Q3_K_M.gguf
gguf · 3,55 GB · SHA-256 a266c4052f3c…2281 · Hugging Face
DescargarKepler-Reasoning-7B.i1-Q3_K_S.gguf
gguf · 3,25 GB · SHA-256 94a663ead877…269e · Hugging Face
DescargarKepler-Reasoning-7B.i1-Q4_K_M.gguf
gguf · 4,36 GB · SHA-256 4940b811856b…aa7b · Hugging Face
DescargarKepler-Reasoning-7B.i1-Q4_K_S.gguf
gguf · 4,15 GB · SHA-256 1519fc71b3a5…c1c6 · Hugging Face
DescargarKepler-Reasoning-7B.i1-Q5_K_M.gguf
gguf · 5,07 GB · SHA-256 666619939352…4ba1 · Hugging Face
DescargarKepler-Reasoning-7B.i1-Q5_K_S.gguf
gguf · 4,95 GB · SHA-256 f1ce4c5af2e3…1e57 · Hugging Face
Descargar--- base_model: aryyanthakrr/Kepler-Reasoning-7B language: - en library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - qwen - mergekit - slerp - math - code - reasoning - local-ai --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss --> <!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: --> weighted/imatrix quants of https://huggingface.co/aryyanthakrr/Kepler-Reasoning-7B <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Kepler-Reasoning-7B-i1-GGUF).*** static quants are available at https://huggingface.co/mradermacher/Kepler-Reasoning-7B-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/Kepler-Reasoning-7B-i1-GGUF/resolve/main/Kepler-Reasoning-7B.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) | | [GGUF](https://huggingface.co/mradermacher/Kepler-Reasoning-7B-i1-GGUF/resolve/main/Kepler-Reasoning-7B.i1-IQ1_S.gguf) | i1-IQ1_S | 2.0 | for the desperate | | [GGUF](https://huggingface.co/mradermacher/Kepler-Reasoning-7B-i1-GGUF/resolve/main/Kepler-Reasoning-7B.i1-IQ1_M.gguf) | i1-IQ1_M | 2.1 | mostly desperate | | [GGUF](https://huggingface.co/mradermacher/Kepler-Reasoning-7B-i1-GGUF/resolve/main/Kepler-Reasoning-7B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.4 | | | [GGUF](https://huggingface.co/mradermacher/Kepler-Reasoning-7B-i1-GGUF/resolve/main/Kepler-Reasoning-7B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.6 | | | [GGUF](https://huggingface.co/mradermacher/Kepler-Reasoning-7B-i1-GGUF/resolve/main/Kepler-Reasoning-7B.i1-IQ2_S.gguf) | i1-IQ2_S | 2.7 | | | [GGUF](https://huggingface.co/mradermacher/Kepler-Reasoning...
Source context: 1281 downloads · 1 likes · Library transformers · Repo mradermacher/Kepler-Reasoning-7B-i1-GGUF
Source context: 7475 downloads · 0 likes · Library transformers · Repo mradermacher/Kepler-Reasoning-7B-i1-GGUF
| i1-IQ2_XS |
| 2.6 |
| GGUF | i1-IQ2_S | 2.7 |
| GGUF | i1-IQ2_M | 2.9 |
| GGUF | i1-Q2_K_S | 2.9 | very low quality |
| GGUF | i1-Q2_K | 3.1 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XXS | 3.2 | lower quality |
| GGUF | i1-IQ3_XS | 3.4 |
| GGUF | i1-Q3_K_S | 3.6 | IQ3_XS probably better |
| GGUF | i1-IQ3_S | 3.6 | beats Q3_K* |
| GGUF | i1-IQ3_M | 3.7 |
| GGUF | i1-Q3_K_M | 3.9 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 4.2 | IQ3_M probably better |
| GGUF | i1-IQ4_XS | 4.3 |
| GGUF | i1-IQ4_NL | 4.5 | prefer IQ4_XS |
| GGUF | i1-Q4_0 | 4.5 | fast, low quality |
| GGUF | i1-Q4_K_S | 4.6 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 4.8 | fast, recommended |
| GGUF | i1-Q4_1 | 5.0 |
| GGUF | i1-Q5_K_S | 5.4 |
| GGUF | i1-Q5_K_M | 5.5 |
| GGUF | i1-Q6_K | 6.4 | practically like static Q6_K |
