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EvoNet 8b Reasoning I1 GGUF | ST Studio
Recursos / EvoNet 8b Reasoning I1 GGUF EvoNet 8b Reasoning I1 GGUF For a convenient overview and download list, visit our model page for this model.
For a convenient overview and download list, visit our model page for this model.
Tipo Other Modelo base EvoNet/EvoNet-8b-Reasoning Versão Revision 8055ac9 Publicador @mradermacher A nota Fonte do modelo
Tipo Other
Tamanho do arquivo 4,78 MB–6,14 GB
Modelo base EvoNet/EvoNet-8b-Reasoning
Versão vRevision 8055ac9
Atualizado 20 de out. de 2026
Downloads 311
Fonte Hugging Face Artefatos de modelo
25 artefatos EvoNet-8b-Reasoning.i1-IQ1_M.gguf
gguf · 2,01 GB · SHA-256 19513e456646…7622 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-IQ1_S.gguf
gguf · 1,88 GB · SHA-256 973312b7e272…686b · Hugging Face
Baixar Trechos de fonte
3 trechos
Usage If 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.
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 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):
FAQ / Model Request
Thanks 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_M.gguf
gguf · 2,75 GB · SHA-256 898e83aad7cd…2721 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-IQ2_S.gguf
gguf · 2,57 GB · SHA-256 0fe90d549b29…1fb5 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-IQ2_XS.gguf
gguf · 2,43 GB · SHA-256 301784677d66…c065 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-IQ2_XXS.gguf
gguf · 2,23 GB · SHA-256 f9497f79f873…74d6 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-IQ3_M.gguf
gguf · 3,52 GB · SHA-256 a98eb449b732…8004 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-IQ3_S.gguf
gguf · 3,43 GB · SHA-256 3ef848fbf526…0868 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-IQ3_XS.gguf
gguf · 3,28 GB · SHA-256 bada68f32edb…0da0 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-IQ3_XXS.gguf
gguf · 3,05 GB · SHA-256 20e75caddfb9…525d · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-IQ4_NL.gguf
gguf · 4,36 GB · SHA-256 bec22e5b40d0…b675 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-IQ4_XS.gguf
gguf · 4,14 GB · SHA-256 78e365a50f99…d1eb · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-Q2_K_S.gguf
gguf · 2,78 GB · SHA-256 b053b4ce6fa1…6e66 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-Q2_K.gguf
gguf · 2,96 GB · SHA-256 3146a2e16a4f…0857 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-Q3_K_L.gguf
gguf · 4,03 GB · SHA-256 d7202f98f9d2…af7e · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-Q3_K_M.gguf
gguf · 3,74 GB · SHA-256 e8d274e99694…b77a · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-Q3_K_S.gguf
gguf · 3,41 GB · SHA-256 3459ad850fe8…3cb2 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-Q4_0.gguf
gguf · 4,35 GB · SHA-256 eefdc8f91429…8f59 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-Q4_1.gguf
gguf · 4,78 GB · SHA-256 8eb5e035d0f8…5a30 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-Q4_K_M.gguf
gguf · 4,58 GB · SHA-256 eb8d23a1e764…d842 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-Q4_K_S.gguf
gguf · 4,37 GB · SHA-256 87f2ecdebd61…da44 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-Q5_K_M.gguf
gguf · 5,34 GB · SHA-256 1221a2215533…9ee5 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-Q5_K_S.gguf
gguf · 5,21 GB · SHA-256 19d6fbead8e7…52c6 · Hugging Face
Baixar EvoNet-8b-Reasoning.i1-Q6_K.gguf
gguf · 6,14 GB · SHA-256 3172f331b348…d220 · Hugging Face
Baixar EvoNet-8b-Reasoning.imatrix.gguf
gguf · 4,78 MB · SHA-256 2a4ce786587a…1039 · Hugging Face
Baixar ---
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
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-Q3_K_S 3.8 IQ3_XS probably better
GGUF i1-IQ3_S 3.8 beats Q3_K*
GGUF i1-Q3_K_M 4.1 IQ3_S probably better
GGUF i1-Q3_K_L 4.4 IQ3_M probably better
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-Q6_K 6.7 practically like static Q6_K
