---
base_model: ZJU-AI4H/Hulu-Med-235A22
language:
- en
library_name: transformers
license: apache-2.0
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
tags:
- medical
- multimodal
- vision-language-model
- image-to-text
- video-understanding
- 3d-understanding
- qwen
- pytorch
---
## About

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static quants of https://huggingface.co/ZJU-AI4H/Hulu-Med-235A22

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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Hulu-Med-235A22-GGUF).***

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Hulu-Med-235A22-i1-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/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.9 | multi-modal supplement |
| [GGUF](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.mmproj-f16.gguf) | mmproj-f16 | 1.3 | multi-modal supplement |
| [GGUF](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q2_K.gguf) | Q2_K | 85.8 |  |
| [GGUF](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q3_K_S.gguf) | Q3_K_S | 101.5 |  |
| [GGUF](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q3_K_M.gguf) | Q3_K_M | 112.5 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q3_K_L.gguf) | Q3_K_L | 121.9 |  |
| [GGUF](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.IQ4_XS.gguf) | IQ4_XS | 126.8 |  |
| [GGUF](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q4_K_S.gguf) | Q4_K_S | 133.8 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q4_K_M.gguf) | Q4_K_M | 142.3 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q5_K_S.gguf) | Q5_K_S | 162.0 |  |
| [GGUF](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q5_K_M.gguf) | Q5_K_M | 166.9 |  |
| [GGUF](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q6_K.gguf) | Q6_K | 193.1 | very good quality |
| [P1](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q8_0.gguf.part1of6) [P2](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q8_0.gguf.part2of6) [P3](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q8_0.gguf.part3of6) [P4](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q8_0.gguf.part4of6) [P5](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q8_0.gguf.part5of6) [P6](https://huggingface.co/mradermacher/Hulu-Med-235A22-GGUF/resolve/main/Hulu-Med-235A22.Q8_0.gguf.part6of6) | Q8_0 | 250.0 | fast, best quality |

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.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](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.

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