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Git Base Textvqa

Developed by Hellraiser24
A visual question answering model fine-tuned on the textvqa dataset based on microsoft/git-base-textvqa, excelling at handling image-based question answering tasks involving text
Large Language Model
Transformers
 OtherOpen Source License:MIT#Text Visual Question Answering#Image Text Understanding#Multimodal Learning
Downloads 19
Release Time : 6/4/2023

Model Overview

This model is a fine-tuned version of the GIT architecture on the TextVQA dataset, specifically designed for visual question answering tasks that require understanding both images and their textual content

Model Features

Joint Text-Image Understanding
Capable of processing both visual information and textual content in images simultaneously
End-to-End Training
Uses a unified Transformer architecture for end-to-end training
Efficient Fine-tuning
Demonstrates good fine-tuning performance on the TextVQA dataset

Model Capabilities

Text recognition in images
Image-text based question answering
Multimodal understanding
Vision-language joint reasoning

Use Cases

Intelligent Assistance
Scene Text Question Answering
Answering questions about text content appearing in images
Achieved a loss value of 0.0472 on the TextVQA evaluation set
Accessibility Technology
Image Text Description
Describing text content in images for visually impaired individuals
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