The answer
Reinforcement Learning from Human Feedback is a method where humans rate model responses to guide training towards helpful answers.
Reinforcement Learning from Human Feedback is a method where humans rate model responses to guide training towards helpful answers.
Base models autocomplete text. Instruct models are fine-tuned to answer questions and follow prompts.
Generally, models with more parameters can store more information and handle complex reasoning, but they require more compute to run.
When a model generates factually incorrect or nonsensical assertions with high confidence.
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