Intuitive Guide to Self-RAG 🐲

Happy Year of the Dragon and happy Valentine’s!🐲💜

The Self-RAG paper was released at the end of last year, and I’m thrilled to share that this groundbreaking model is now accessible through LlamaIndex’s LlamaPack.

Check it out! 👇

🚀What is Self-RAG?

Self-RAG is a revolutionary framework designed to enhance the quality and factuality of language models through a combination of retrieval and self-reflection. Unlike traditional approaches, Self-RAG trains a single arbitrary language model that adaptively retrieves passages on-demand. This model then generates and reflects on the retrieved passages and its own generations using special tokens known as reflection tokens.

🔍Key Features:

• Adaptive Retrieval: Self-RAG dynamically retrieves passages as needed, adapting to the context of the task at hand.
• Self-Reflection: The model generates and reflects on retrieved passages, fostering a controllable and tailored behavior during the inference phase.

🎉Performance Breakthrough:

Results from experiments with Self-RAG, featuring 7B and 13B parameters, showcase its superiority over state-of-the-art LLMs and retrieval-augmented models. Self-RAG outperforms ChatGPT and retrieval-augmented Llama2-chat on various tasks, including Open-domain QA, reasoning, and fact verification. Notably, it demonstrates significant improvements…