How to Train a Custom LLM/ChatGPT on Your Documents (Dec 2023)
Analysis
The article poses a practical question about the current best practices for using a custom dataset with an LLM, specifically focusing on non-hallucinating and accurate results. It acknowledges the rapid evolution of the field by referencing an older thread and seeking updated advice. The question is clarified to include Retrieval-Augmented Generation (RAG) approaches, indicating a focus on practical application rather than full model training.
Key Takeaways
- •The primary goal is to find the most effective method for using custom documents with an LLM.
- •The focus is on achieving accurate and reliable results, minimizing hallucinations.
- •The question is open to various approaches, including RAG.
- •The context is the rapidly changing landscape of LLMs in December 2023.
Reference
“What is the best approach for feeding custom set of documents to LLM and get non-halucinating and decent result in Dec 2023?”