Reward model
Also: reward models
A helper model that scores answers so the main model can learn what people like.
The fuller definition
A reward model assigns a numerical score intended to represent a training preference or objective. Its score can guide optimization of another model.
Supply instructions and examples each time. Nothing in the model changes.
Fetch current documents and put them in context. Facts can change daily.
Train the parameters on examples. Changes behaviour and style; poor at keeping facts current.
Most legal tasks need the first two. Fine-tuning is a project, with data, evaluation, and maintenance, and it is the wrong tool for facts that change.
A concrete example
A reward model scores candidate answers for how well they match preferences learned from feedback.
The distinction that matters
A high reward score is not a universal truth or quality guarantee; the scoring proxy can be imperfect.
Related terms
Reinforcement learning from human feedback (RLHF)
Training that uses people's ratings of model answers. It helps steer the model toward replies people prefer.
Training & generationAlignment
Work to make a model act as people intend. For example, it should follow rules and avoid harm. This is a goal, not a promise.
Reliability & securityEvaluation (eval)
Testing an AI tool on a set of tasks to see how well it actually does.
Where it is taught
How models learn from examplesSource and further reading
Hugging Face · LLM courseThe definition and example are written for this library. The link gives background, official documentation or legal authority as labelled. Legal scope depends on the jurisdiction and current text; product features depend on release and settings.