Prompt Engineering Guide
πŸ˜ƒ Basics
πŸ’Ό Applications
πŸ§™β€β™‚οΈ Intermediate
🧠 Advanced
Special Topics
🌱 New Techniques
πŸ€– Agents
βš–οΈ Reliability
πŸ–ΌοΈ Image Prompting
πŸ”“ Prompt Hacking
πŸ”¨ Tooling
πŸ’ͺ Prompt Tuning
πŸ—‚οΈ RAG
🎲 Miscellaneous
Models
πŸ“ Language Models
Resources
πŸ“™ Vocabulary Resource
πŸ“š Bibliography
πŸ“¦ Prompted Products
πŸ›Έ Additional Resources
πŸ”₯ Hot Topics
✨ Credits

Reinforcement Learning from Human Feedback (RLHF)

Reading Time: 1 minute
Last updated on November 12, 2024

Valeriia Kuka

Reinforcement Learning from Human Feedback is a method for fine tuning LLMs according to human preference data.

Valeriia Kuka

Valeriia Kuka, Head of Content at Learn Prompting, is passionate about making AI and ML accessible. Valeriia previously grew a 60K+ follower AI-focused social media account, earning reposts from Stanford NLP, Amazon Research, Hugging Face, and AI researchers. She has also worked with AI/ML newsletters and global communities with 100K+ members and authored clear and concise explainers and historical articles.