RLHF vs Direct Preference Optimization
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RLHF
technology
Direct Preference Optimization
technology
Ecosystem
RLHF
No mapped relationships
Direct Preference Optimization
RLHF
In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves training a reward model to represent preferences, which can then be used to train other models through reinforcement learning.
Direct Preference Optimization
Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in computer science that develops and studies methods and so
Recent Events
RLHF
No timeline events
Direct Preference Optimization
Technical guide published providing complete code-first walkthrough for fine-tuning Llama 3 with DPO