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For a convenient overview and download list, visit our model page for this model.
Model source
Source description
weighted/imatrix quants of https://huggingface.co/EvoNet/EvoNet-8b-Reasoning
For a convenient overview and download list, visit our model page for this model.
static quants are available at
Sources
1 sourceVerified Oct 20
Model artifacts
25 artifactsSource excerpts
3 excerptsIf 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 | 2.1 | for the desperate |
| GGUF | i1-IQ1_M | 2.3 | mostly desperate |
| GGUF | i1-IQ2_XXS | 2.5 | |
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.
EvoNet-8b-Reasoning.i1-IQ2_XXS.gguf
gguf · 2.23 GB · SHA-256 f9497f79f873…74d6 · Hugging Face
DownloadEvoNet-8b-Reasoning.i1-IQ3_XXS.gguf
gguf · 3.05 GB · SHA-256 20e75caddfb9…525d · Hugging Face
Download--- base_model: EvoNet/EvoNet-8b-Reasoning language: - vi - en library_name: transformers license: llama3.1 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - reasoning - cybersecurity - pentest - evonet - llama-3.1 --- ## 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/EvoNet/EvoNet-8b-Reasoning <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#EvoNet-8b-Reasoning-i1-GGUF).*** static quants are available at https://huggingface.co/mradermacher/EvoNet-8b-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/EvoNet-8b-Reasoning-i1-GGUF/resolve/main/EvoNet-8b-Reasoning.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) | | [GGUF](https://huggingface.co/mradermacher/EvoNet-8b-Reasoning-i1-GGUF/resolve/main/EvoNet-8b-Reasoning.i1-IQ1_S.gguf) | i1-IQ1_S | 2.1 | for the desperate | | [GGUF](https://huggingface.co/mradermacher/EvoNet-8b-Reasoning-i1-GGUF/resolve/main/EvoNet-8b-Reasoning.i1-IQ1_M.gguf) | i1-IQ1_M | 2.3 | mostly desperate | | [GGUF](https://huggingface.co/mradermacher/EvoNet-8b-Reasoning-i1-GGUF/resolve/main/EvoNet-8b-Reasoning.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.5 | | | [GGUF](https://huggingface.co/mradermacher/EvoNet-8b-Reasoning-i1-GGUF/resolve/main/EvoNet-8b-Reasoning.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.7 | | | [GGUF](https://huggingface.co/mradermacher/EvoNet-8b-Reasoning-i1-GGUF/resolve/main/EvoNet-8b-Reasoning.i1-IQ2_S.gguf) | i1-IQ2_S | 2.9 | | | [GGUF](https://huggingface.co/mradermacher/EvoNet-8b-Reasoning-i1-GGUF/r...
Source context: 311 downloads · 0 likes · Library transformers · Repo mradermacher/EvoNet-8b-Reasoning-i1-GGUF
Source context: 64 downloads · 0 likes · Library transformers · Repo mradermacher/EvoNet-8b-Reasoning-i1-GGUF
| i1-IQ2_XS |
| 2.7 |
| GGUF | i1-IQ2_S | 2.9 |
| GGUF | i1-IQ2_M | 3.0 |
| GGUF | i1-Q2_K_S | 3.1 | very low quality |
| GGUF | i1-Q2_K | 3.3 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XXS | 3.4 | lower quality |
| GGUF | i1-IQ3_XS | 3.6 |
| GGUF | i1-Q3_K_S | 3.8 | IQ3_XS probably better |
| GGUF | i1-IQ3_S | 3.8 | beats Q3_K* |
| GGUF | i1-IQ3_M | 3.9 |
| GGUF | i1-Q3_K_M | 4.1 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 4.4 | IQ3_M probably better |
| GGUF | i1-IQ4_XS | 4.5 |
| GGUF | i1-Q4_0 | 4.8 | fast, low quality |
| GGUF | i1-IQ4_NL | 4.8 | prefer IQ4_XS |
| GGUF | i1-Q4_K_S | 4.8 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 5.0 | fast, recommended |
| GGUF | i1-Q4_1 | 5.2 |
| GGUF | i1-Q5_K_S | 5.7 |
| GGUF | i1-Q5_K_M | 5.8 |
| GGUF | i1-Q6_K | 6.7 | practically like static Q6_K |
