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TL;DR Agentic workloads change the traffic an inference server sees. Unlike single-turn chat, an agent session can involve a large initial prefill, repeated model calls, and subagents running in parallel,... The post Session-Aware Agentic Inference with NVIDIA Dynamo appeared first on PyTorch.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them.
This is the final post in a four-part series about post-training. If you missed them, check out part 1, part 2, and part 3. Time to get your hands dirty! I’ll take you through implementing the key pieces of the classic ChatGPT pipeline: SFT, then reward model training, then PPO.
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