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Blip Image Captioning Large Mocha

Developed by moranyanuka
This is the official fine-tuned version of the BLIP-Large model, optimized using the MOCHa reinforcement learning framework on the MS-COCO dataset to mitigate open-vocabulary description hallucination issues
Downloads 188
Release Time : 12/19/2023

Model Overview

An image captioning generation model based on the BLIP-Large architecture, supporting both conditional and unconditional image caption generation

Model Features

MOCHa Fine-tuning
Fine-tuned on the MS-COCO dataset using the MOCHa reinforcement learning framework
Mitigating Description Hallucination
Specifically optimized to address open-vocabulary description hallucination issues
Dual-mode Generation
Supports both conditional and unconditional image caption generation methods

Model Capabilities

Image Caption Generation
Conditional Text Generation
Vision-Language Understanding

Use Cases

Image Understanding
Automatic Image Tagging
Generates accurate descriptive text for images
Produces natural language descriptions that match image content
Assisting Visually Impaired Users
Converts visual content into textual descriptions
Helps visually impaired individuals understand image content
Content Creation
Social Media Content Generation
Automatically generates captions for uploaded images
Improves content creation efficiency
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