Vision-Language Model (VLM) from Scratch

A comprehensive project to develop a Vision-Language Model from scratch. This model will be capable of understanding and generating text based on visual inputs, and vice versa. The project focuses on implementing cutting-edge architectures while maintaining transparency in the development process.

Project Goals

1. Implement a transformer-based architecture for image and text processing
2. Train on diverse datasets for robust performance
3. Achieve competitive performance on standard VLM benchmarks
4. Open source the implementation with detailed documentation

Technical Details

The model architecture consists of:

• Vision Transformer (ViT) for image encoding
• BERT-style transformer for text processing
• Cross-attention mechanisms for multimodal fusion

Implementation Progress

Current progress includes:

• [ ] Basic transformer architecture implementation
• [ ] Data pipeline setup
• [ ] Training infrastructure preparation
• [ ] Model evaluation framework

Resources

• Project Repository
• Documentation
• Research Papers