OmniVL Guard 8B GGUF
For a convenient overview and download list, visit our model page for this model.
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 717 MB–15,3 GB
- Modelo base
- SJJ0854/OmniVL-Guard-8B
- Versión
- vRevision a229655
- Actualizado
- 4 oct 2026
- Publicador
- @mradermacher
- Descargas
- 298
- Parámetros
- 8B
- Fuente
- Hugging Face
Descripción de la fuente
About
static quants of https://huggingface.co/SJJ0854/OmniVL-Guard-8B
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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 | mmproj-Q8_0 | 0.9 | multi-modal supplement |
| GGUF | mmproj-f16 | 1.3 | multi-modal supplement |
| GGUF | Q2_K | 3.4 | |
| GGUF | Q3_K_S | 3.9 | |
| GGUF | Q3_K_M | 4.2 | lower quality |
| GGUF | Q3_K_L | 4.5 | |
| GGUF | IQ4_XS | 4.7 | |
| GGUF | Q4_K_S | 4.9 | fast, recommended |
| GGUF | Q4_K_M | 5.1 | fast, recommended |
| GGUF | Q5_K_S | 5.8 | |
| GGUF | Q5_K_M | 6.0 | |
| GGUF | Q6_K | 6.8 | very good quality |
| GGUF | Q8_0 | 8.8 | fast, best quality |
| GGUF | f16 | 16.5 | 16 bpw, overkill |
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
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, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 27 ago
Artefactos del modelo
14 artefactos
Artefactos del modelo
14 artefactosExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- base_model: SJJ0854/OmniVL-Guard-8B language: - en library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - vision - multimodal - safety - guard-model - icml-2026 --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> <!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: --> static quants of https://huggingface.co/SJJ0854/OmniVL-Guard-8B <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#OmniVL-Guard-8B-GGUF).*** weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion. ## 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/OmniVL-Guard-8B-GGUF/resolve/main/OmniVL-Guard-8B.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.9 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/OmniVL-Guard-8B-GGUF/resolve/main/OmniVL-Guard-8B.mmproj-f16.gguf) | mmproj-f16 | 1.3 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/OmniVL-Guard-8B-GGUF/resolve/main/OmniVL-Guard-8B.Q2_K.gguf) | Q2_K | 3.4 | | | [GGUF](https://huggingface.co/mradermacher/OmniVL-Guard-8B-GGUF/resolve/main/OmniVL-Guard-8B.Q3_K_S.gguf) | Q3_K_S | 3.9 | | | [GGUF](https://huggingface.co/mradermacher/OmniVL-Guard-8B-GGUF/resolve/main/OmniVL-Guard-8B.Q3_K_M.gguf) | Q3_K_M | 4.2 | lower quality | | [GGUF](https://huggingface.co/mradermacher/OmniVL-Guard-8B-GGUF/resolve/main/OmniVL-Guard-8B.Q3_K_L.gguf) | Q3_K_L | 4.5 | | | [GGUF](https://huggingface.co/mradermacher/OmniVL-Guard-8B-GGUF/resolve/main/OmniVL-Guard-8B.IQ4_XS.gguf) | IQ4_XS | 4.7 | | | [GGUF](https://huggingface.co...
Source context: 298 downloads · 1 likes · Library transformers · Repo mradermacher/OmniVL-Guard-8B-GGUF
Source context: 20 downloads · 1 likes · Library transformers · Repo mradermacher/OmniVL-Guard-8B-GGUF
