Scale RLHF training with Ray

Distribute RLHF training across multi-GPU clusters

Scaling PPO/GRPO/RLOO/DPO training to 70B+ models with multi-node vLLM.

• · Base model (7B-70B+)
• · Preference dataset
• · Reward model (optional)
• · Ray cluster config

• · RLHF-trained checkpoint
• · Training logs
• · vLLM inference artifact

• · OpenRLHF
• · Ray
• · vLLM
• · DeepSpeed ZeRO-3
• · torch

• · Ray cluster running
• · vLLM accessible
• · Preference dataset ready
• · GPU >= 24GB per node

• · vLLM engine dies
• · ZeRO-3 CPU RAM exhausted
• · Preference format mismatch
• · Colocate OOM

• · Orchestra skill
• · OpenRLHF with Ray/vLLM
• · 2× faster than DeepSpeedChat
• · Production-tested