M

Microsoft Git Base

Developed by seckmaster
GIT is a Transformer-based generative image-to-text model capable of converting visual content into textual descriptions.
Downloads 18
Release Time : 12/4/2024

Model Overview

GIT (GenerativeImage2Text) is a Transformer decoder model that combines CLIP image tokens and text tokens, trained via teacher forcing, enabling tasks such as image caption generation and visual question answering.

Model Features

Bidirectional Image Attention
The model employs bidirectional attention masking for image patch tokens to fully comprehend image content.
Causal Text Generation
During text generation, it can only access previous text tokens, ensuring coherent textual descriptions.
Multi-task Support
Capable of handling various tasks including image caption generation, visual question answering, and even image classification.

Model Capabilities

Image Caption Generation
Visual Question Answering
Image Classification (via text generation)
Video Caption Generation

Use Cases

Content Generation
Automatic Image Tagging
Generate accurate textual descriptions for images
Can be used in image retrieval systems and accessibility applications
Visual Question Answering
Image Content Q&A
Answer natural language questions about image content
Applicable in smart assistants and educational applications
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