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Qwen2.5 VL 7B Captioner Relaxed GGUF
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Qwen2.5 VL 7B Captioner Relaxed GGUF

Developed by samgreen
Qwen2.5-VL-7B-Captioner-Relaxed is a multimodal vision-language model based on the Qwen2.5 architecture, focusing on image-to-text generation tasks.
Image-to-Text EnglishOpen Source License:Apache-2.0#Multimodal Image Captioning#Low-resource Quantization Deployment#Chinese Image Understanding
Downloads 320
Release Time : 3/23/2025

Model Overview

This model is a multimodal vision-language model capable of generating corresponding textual descriptions from input images. It is based on the Qwen2.5 architecture and optimized to provide more natural image captioning capabilities.

Model Features

Multimodal Support
Capable of processing both image and text inputs to generate coherent textual descriptions.
Optimized Image Captioning
Specially optimized to generate more natural and accurate image descriptions.
Easy Deployment
Supports inference via llama.cpp and koboldcpp, making it easy to deploy in various environments.

Model Capabilities

Image Caption Generation
Multimodal Reasoning
Text Generation

Use Cases

Content Generation
Automatic Image Tagging
Generate detailed textual descriptions for images, useful for content management systems or social media.
Produces natural and accurate image descriptions.
Assistive Tools
Visual Assistance
Provide textual descriptions of images for visually impaired users.
Helps visually impaired users understand image content.
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