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Definition

RLHF

Reinforcement Learning from Human Feedback (RLHF) is a training methodology used to align LLMs with human values and preferences. It uses human evaluations to train a reward model, which then guides the LLM to generate helpful, harmless, and honest outputs.

Frequently Asked Questions

Why was RLHF used for ChatGPT?

Raw pre-trained models generate text based on next-word probability, which often leads to offensive or unhelpful text. RLHF aligns the model to act as a conversational assistant.

What is a Reward Model in RLHF?

A secondary network trained on human preferences that scores model responses. This score is used as a reward signal in reinforcement learning.

Quick Facts

  • CategoryModel Training
  • Key ApplicationModel alignment, safety constraint training, and conversational tuning

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