NayanaVQA GGUF
For a convenient overview and download list, visit our model page for this model.
Source du modèle
- Type
- Other
- Taille du fichier
- 2,57–12,8 GB
- Modèle de base
- Nayana-cognitivelab/NayanaVQA
- Version
- vRevision 3e50d57
- Mis à jour
- 23 oct. 2026
- Téléchargements
- 140
- Source
- Hugging Face
Description de la source
About
static quants of https://huggingface.co/Nayana-cognitivelab/NayanaVQA
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 | Q2_K | 2.9 | |
| GGUF | Q3_K_S | 3.4 | |
| GGUF | Q3_K_M | 3.5 | lower quality |
| GGUF | Q3_K_L | 3.7 | |
| GGUF | IQ4_XS | 4.0 | |
| GGUF | Q4_K_S | 4.2 | fast, recommended |
| GGUF | Q4_K_M | 4.3 | fast, recommended |
| GGUF | Q5_K_S | 5.0 | |
| GGUF | Q5_K_M | 5.0 | |
| GGUF | Q6_K | 5.8 | very good quality |
| GGUF | Q8_0 | 7.5 | fast, best quality |
| GGUF | f16 | 13.8 | 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.
Sources
1 source
Sources
1 sourceVérifié 23 oct.
Download files
Artefacts du modèle
12 artefacts
Artefacts du modèle
12 artefactsExtraits de sources
3 extraits
Extraits de sources
3 extraits--- base_model: Nayana-cognitivelab/NayanaVQA datasets: - Nayana-cognitivelab/NayanaVQA-SFT language: - kn library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - text-generation-inference - transformers - unsloth - gemma3n - vqa - document-vqa - visual-question-answering - vision-language - kannada --- ## 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/Nayana-cognitivelab/NayanaVQA <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#NayanaVQA-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/NayanaVQA-GGUF/resolve/main/NayanaVQA.Q2_K.gguf) | Q2_K | 2.9 | | | [GGUF](https://huggingface.co/mradermacher/NayanaVQA-GGUF/resolve/main/NayanaVQA.Q3_K_S.gguf) | Q3_K_S | 3.4 | | | [GGUF](https://huggingface.co/mradermacher/NayanaVQA-GGUF/resolve/main/NayanaVQA.Q3_K_M.gguf) | Q3_K_M | 3.5 | lower quality | | [GGUF](https://huggingface.co/mradermacher/NayanaVQA-GGUF/resolve/main/NayanaVQA.Q3_K_L.gguf) | Q3_K_L | 3.7 | | | [GGUF](https://huggingface.co/mradermacher/NayanaVQA-GGUF/resolve/main/NayanaVQA.IQ4_XS.gguf) | IQ4_XS | 4.0 | | | [GGUF](https://huggingface.co/mradermacher/NayanaVQA-GGUF/resolve/main/NayanaVQA.Q4_K_S.gguf) | Q4_K_S | 4.2 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/NayanaVQA-GGUF/resolve/main/NayanaVQA.Q4_K_M.gguf) | Q4_K_M | 4.3 | fast, recommended | | [GGUF]...
Source context: 140 downloads · 0 likes · Pipeline visual-question-answering · Library transformers · Repo mradermacher/NayanaVQA-GGUF
Source context: 127 downloads · 0 likes · Pipeline visual-question-answering · Library transformers · Repo mradermacher/NayanaVQA-GGUF
