ISSUES.md

Planned Issues and Enhancements

Please create the following issues on the GitHub repository:

Issue 1: Implement Training Pipeline

Title: Implement Training Pipeline for LLaVA Model

Description: This issue is for implementing a complete training pipeline for the LLaVA model, including both the feature alignment stage and visual instruction tuning stage.

Tasks:

• Create data loaders for pretraining datasets
• Implement feature alignment training loop
• Implement visual instruction tuning training loop
• Add support for distributed training
• Add checkpointing and resuming functionality
• Create training configuration files
• Document the training process

Labels: enhancement, training

Issue 2: Add Support for Model Quantization

Title: Add Support for Model Quantization

Description: Implement more advanced quantization techniques to reduce the memory footprint and improve inference speed.

Tasks:

• Implement INT8 quantization
• Implement INT4 quantization
• Add support for GPTQ quantization
• Add support for AWQ quantization
• Benchmark performance and accuracy trade-offs
• Document quantization options

Labels: enhancement, optimization

Issue 3: Improve Evaluation Suite

Title: Improve Evaluation Suite

Description: Enhance the evaluation capabilities to support more benchmarks and metrics.

Tasks:

• Add support for VQAv2 benchmark
• Add support for GQA benchmark
• Add support for TextVQA benchmark
• Implement BLEU, ROUGE, and other NLG metrics
• Create visualizations for evaluation results
• Add support for batch evaluation

Labels: enhancement, evaluation

Issue 4: Create Comprehensive Documentation

Title: Create Comprehensive Documentation

Description: Improve the project documentation to make it more accessible and user-friendly.

Tasks:

• Create detailed API documentation
• Add more examples and tutorials
• Create a documentation website using GitHub Pages
• Add diagrams explaining the architecture
• Document all configuration options
• Create a troubleshooting guide

Labels: documentation

Issue 5: Implement Web Demo

Title: Implement Web Demo

Description: Create a web demo that allows users to try the model without installing anything.

Tasks:

• Create a simple web interface
• Deploy the model to Hugging Face Spaces
• Add example images for testing
• Support image upload
• Support different model configurations
• Add visualization of attention maps

Labels: enhancement, demo