TreeVGR 7B CI I1 GGUF
For a convenient overview and download list, visit our model page for this model.
Source du modèle
- Type
- Other
- Taille du fichier
- 1,77–5,82 GB
- Modèle de base
- HaochenWang/TreeVGR-7B-CI
- Version
- vRevision c25ef33
- Mis à jour
- 23 oct. 2026
- Téléchargements
- 700
- Source
- Hugging Face
Description de la source
About
weighted/imatrix quants of https://huggingface.co/HaochenWang/TreeVGR-7B-CI
For a convenient overview and download list, visit our model page for this model.
static quants are available at https://huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF
This is a vision model - mmproj files (if any) will be in the static repository.
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 | i1-IQ1_S | 2.0 | for the desperate |
| GGUF | i1-IQ1_M | 2.1 | mostly desperate |
| GGUF | i1-IQ2_XXS | 2.4 | |
| 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 |
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. 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.
Sources
1 source
Sources
1 sourceVérifié 23 oct.
Download files
Artefacts du modèle
24 artefacts
Artefacts du modèle
24 artefactsExtraits de sources
3 extraits
Extraits de sources
3 extraits--- base_model: HaochenWang/TreeVGR-7B-CI datasets: - HaochenWang/TreeBench - HaochenWang/TreeVGR-RL-37K - HaochenWang/TreeVGR-SFT-35K language: - en library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - visual-question-answering - visual-grounding - visual-reasoning - qwen --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss --> weighted/imatrix quants of https://huggingface.co/HaochenWang/TreeVGR-7B-CI <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#TreeVGR-7B-CI-i1-GGUF).*** static quants are available at https://huggingface.co/mradermacher/TreeVGR-7B-CI-GGUF **This is a vision model - mmproj files (if any) will be in the [static repository](https://huggingface.co/mradermacher/TreeVGR-7B-CI-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/TreeVGR-7B-CI-i1-GGUF/resolve/main/TreeVGR-7B-CI.i1-IQ1_S.gguf) | i1-IQ1_S | 2.0 | for the desperate | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-i1-GGUF/resolve/main/TreeVGR-7B-CI.i1-IQ1_M.gguf) | i1-IQ1_M | 2.1 | mostly desperate | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-i1-GGUF/resolve/main/TreeVGR-7B-CI.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.4 | | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-i1-GGUF/resolve/main/TreeVGR-7B-CI.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.6 | | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-i1-GGUF/resolve/main/TreeVGR-7B-CI.i1-IQ2_S.gguf) | i1-IQ2_S | 2.7 | | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-i1-GGUF/resolve/main/TreeVGR-7B-CI.i1-IQ2_M.gguf) | i1-IQ2_M | 2.9 | | | [GGUF](https://huggingface.co/mradermacher/TreeVGR-7B-CI-i1-GGUF/resolve/main/TreeVGR-7B-CI.i1-Q2_K_S.gguf) | i1-Q2_K_S | 2.9 | very low quality | | [GGUF](https://huggingface.co/mraderma...
Source context: 700 downloads · 1 likes · Pipeline visual-question-answering · Library transformers · Repo mradermacher/TreeVGR-7B-CI-i1-GGUF
Source context: 589 downloads · 1 likes · Pipeline visual-question-answering · Library transformers · Repo mradermacher/TreeVGR-7B-CI-i1-GGUF
