Massive RAG Pipeline Built on Epstein Files: 2 Million+ Pages Processed!
research#rag📝 Blog|Analyzed: Feb 11, 2026 06:03•
Published: Feb 11, 2026 05:03
•1 min read
•r/learnmachinelearningAnalysis
This project showcases the power of applying cutting-edge techniques to real-world, large-scale datasets. The developer is actively experimenting with optimizing every layer of the RAG pipeline, promising exciting advancements in semantic search and question-answering capabilities. This open-source project is a fantastic opportunity to learn and contribute to advancements in information retrieval.
Key Takeaways
- •The project uses a massive 2 million+ page dataset for Retrieval-Augmented Generation (RAG).
- •It focuses on optimizing the entire data processing pipeline for better performance.
- •The project is open source, encouraging collaboration and further development.
Reference / Citation
View Original"Took the Epstein Files dataset from Hugging Face (teyler/epstein-files-20k) – 2 million+ pages of trending news and documents."