Dermatech-Qwen2-VL-2B-GGUF open-source multimodal model, supporting text generation, image-to-text conversion, and visual question answering

Dermatech Qwen2 VL 2B GGUF

Developed by mradermacher

This is a multimodal model based on the Qwen2 architecture, supporting text generation, image-to-text, and visual question answering tasks, with multiple quantized versions to meet diverse needs.

Image-to-Text English#Dermatology Multimodal #Lightweight Visual Question Answering #Medical Image Captioning

Downloads 42

Release Time : 12/15/2024

Model Overview

Dermatech-Qwen2-VL-2B is a 2B-parameter multimodal model that supports both text and visual inputs, suitable for text generation and visual question answering tasks in the medical dermatology field.

Model Features

Multimodal Support

Processes both text and visual inputs simultaneously, enabling cross-modal understanding and generation

Multiple Quantized Versions

Offers various quantization options from Q2_K to Q8_0, balancing model size and performance

Medical Domain Optimization

Specially optimized for dermatology medical scenarios, suitable for professional applications

Model Capabilities

Text generation

Image caption generation

Visual question answering

Multimodal understanding

Use Cases

Medical Assistance

Dermatological Diagnosis Assistance

Generates diagnostic suggestions by analyzing skin lesion images

Medical Report Generation

Automatically generates medical reports based on visual examinations and text inputs

Education

Medical Education

Provides interactive learning for medical students with dermatology case studies

🚀 Dermatech-Qwen2-VL-2B Quantized Model

This project provides static quantizations of the Dermatech-Qwen2-VL-2B model, offering various quantized versions for different usage scenarios.

📚 Documentation

Model Information

Property	Details
Base Model	Rewatiramans/Dermatech-Qwen2-VL-2B
Language	en
Library Name	transformers
Quantized By	mradermacher
Tags	text-generation, image-to-text, visual-question-answering, multimodal, qwen, lora

About

Static quants of https://huggingface.co/Rewatiramans/Dermatech-Qwen2-VL-2B. Weighted/imatrix quants are available at https://huggingface.co/mradermacher/Dermatech-Qwen2-VL-2B-i1-GGUF.

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	0.8
GGUF	Q3_K_S	0.9
GGUF	Q3_K_M	0.9	lower quality
GGUF	Q3_K_L	1.0
GGUF	IQ4_XS	1.0
GGUF	Q4_K_S	1.0	fast, recommended
GGUF	Q4_K_M	1.1	fast, recommended
GGUF	Q5_K_S	1.2
GGUF	Q5_K_M	1.2
GGUF	Q6_K	1.4	very good quality
GGUF	mmproj-fp16	1.4	vision supplement
GGUF	Q8_0	1.7	fast, best quality
GGUF	f16	3.2	16 bpw, overkill

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

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.

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