Individual skill
post-training-torchforge
Provides guidance for PyTorch-native agentic RL using torchforge, Meta's library separating infra from algorithms. Use when you want clean RL abstractions, easy algorithm experimentation, or scalable training with Monarch and TorchTitan.
skills-imported/post-training-torchforge/SKILL.md
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- agent-skills Repository topic
- ai-agents Repository topic
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- reinforcement-learning Declared skill tag
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Read excerpt
# torchforge: PyTorch-Native Agentic RL Library
torchforge is Meta's PyTorch-native RL library that separates infrastructure concerns from algorithm concerns. It enables rapid RL research by letting you focus on algorithms while handling distributed training, inference, and weight sync automatically.
## When to Use torchforge
**Choose torchforge when you need:**
- Clean separation between RL algorithms and infrastructure
- PyTorch-native abstractions (no Ray dependency)
- Easy algorithm experimentation (GRPO, DAPO, SAPO in ~100 lines)
- Scalable training with Monarch actor system
- Integration with TorchTitan for model parallelism
**Consider alternatives when:**