Learn how to productionize large language models using distributed post-training and inference optimization techniques. Participants will explore advanced LLM post-training techniques, including agentic reinforcement learning with SkyRL.
Hands-on topics include:
Intro to LLM post-training
Intro to RLVR (with GRPO)
Recent development of LLM post-training:
On-policy distillation (OPD) and Multi-teacher On-policy distillation (MOPD)
Case study: Post-training a terminal agent
Building evals
Building custom environments
RL systems
Demo walkthrough
Intro to SkyRL
Full Async RL with SkyRL
Performance monitoring and tuning for RL rollouts