This repo is a collection implementations of some of the best and my favourite research publications in the space of AI in recent years with focus on Generative AI. All implementations are in Python. Each folder corresponds to one paper and aims to capture the core algorithmic ideas with practical, minimal code (I have skipped experimentations/comparisons, only focusing on the core methodology)
- Each folder includes its own
README.mdwith paper-specific notes, differences in the implementations, and how to run - Scripts are kept simple and something you can implement and play around with too.
- Algorithmic flow as close and faithful to the original paper as possible
- You can expect explicit caveats like when a paper uses finetuning, I might have used off the shelf LLM API, but I have mentioned all caveats/exceptions I made to the original paper in the respective READMEs