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Coders In Hoods

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Course overview

Fine-Tuning and RL for Agents

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1 · Decide and prepare

1Prompt, optimise or train?
2Training data from traces

2 · Supervised and preference fine-tuning

3SFT with LoRA on a free GPU
4Preference optimisation

3 · Reinforcement learning for agents

5GRPO in practice
6Designing rewards
7Multi-turn RL environments
Exercise answers
- Answer: Wrap the triage tools as a TRL environment and run multi-turn GRPO
- Answer: Measure step-level credit on your own rollouts
8Reward hacking, regressions and shipping

CapstoneTrain a triage model, then decide whether to ship it Reference implementation

Answers Lesson 7: Multi-turn RL environments

Step-by-step answer

Stretch 60 min6 steps

Measure step-level credit on your own rollouts

Back to the exercise

Previous answerWrap the triage tools as a TRL environment and run multi-turn GRPO Next answer Hunt the escalation hack and fix the reward

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