Fine-tune language models with custom rewards.
Guides the implementation of language-model fine-tuning with TRL using custom rewards for reasoning and task-specific behavior.
When to use it
Use when training models to follow output formats, solve verifiable tasks, improve reasoning, learn domain-specific behavior, or balance multiple objectives.
It changes how the agent implements GRPO training by prescribing a sequential workflow, reusable templates, and incremental reward-function development.
What you provide
Declares transformers version 4.47.0 or later as a dependency.
Declares trl version 0.14.0 or later as a dependency.
This skill
wandb
Sends training logs to wandb
Qwen/Qwen2.5-1.5B-Instruct
Downloads model weights and tokenizer