# Qwen2.5 VL 7B Abliterated Caption It GGUF

URL: https://interfaze.ai/models/mradermacherqwen25-vl-7b-abliterated-caption-it-gguf

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Qwen2.5 VL 7B Abliterated Caption It GGUF by mradermacher, a image-to-text model with multimodal capabilities. Understand and compare multimodal features, benchmarks, and capabilities.

## Comparison

| Feature | Qwen2.5 VL 7B Abliterated Caption It GGUF | Interfaze |
| --- | --- | --- |
| Input Modalities | image, text | image, text, audio, video, document |
| Native OCR | No | Yes |
| Long Document Processing | No | Yes |
| Language Support | 3 partial | 162+ |
| Native Speech-to-Text | No | Yes |
| Native Object Detection | No | Yes |
| Guardrail Controls | No | Yes |
| Context Input Size | unknown | 1M |
| Tool Calling | No | Tool calling supported + built in browser, code execution and web search |

### Scaling

| Feature | Qwen2.5 VL 7B Abliterated Caption It GGUF | Interfaze |
| --- | --- | --- |
| Scaling | Self-hosted/Provider-hosted with quantization | Unlimited |

[Try Interfaze](https://interfaze.ai/dashboard)[Read the Docs](https://interfaze.ai/docs)

View model card on [Hugging Face](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Abliterated-Caption-it-GGUF)

## About

static quants of [https://huggingface.co/prithivMLmods/Qwen2.5-VL-7B-Abliterated-Caption-it](https://huggingface.co/prithivMLmods/Qwen2.5-VL-7B-Abliterated-Caption-it)

_**For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Qwen2.5-VL-7B-Abliterated-Caption-it-GGUF).**_

weighted/imatrix quants are available at [https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Abliterated-Caption-it-i1-GGUF](https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Abliterated-Caption-it-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 | mmproj-Q8\_0 | 1.0 | multi-modal supplement |
| GGUF | mmproj-f16 | 1.5 | multi-modal supplement |
| GGUF | Q2\_K | 3.1 |  |
| GGUF | Q3\_K\_S | 3.6 |  |
| GGUF | Q3\_K\_M | 3.9 | lower quality |
| GGUF | Q3\_K\_L | 4.2 |  |
| GGUF | IQ4\_XS | 4.4 |  |
| GGUF | Q4\_K\_S | 4.6 | fast, recommended |
| GGUF | Q4\_K\_M | 4.8 | fast, recommended |
| GGUF | Q5\_K\_S | 5.4 |  |
| GGUF | Q5\_K\_M | 5.5 |  |
| GGUF | Q6\_K | 6.4 | very good quality |
| GGUF | Q8\_0 | 8.2 | fast, best quality |
| GGUF | f16 | 15.3 | 16 bpw, overkill |

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](https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9)

## FAQ / Model Request

See [https://huggingface.co/mradermacher/model\_requests](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.

## Want more deterministic results?

[Try Interfaze](https://interfaze.ai/dashboard)[Read the Docs](https://interfaze.ai/docs)