Modal Releases Training Gym SDK to Simplify RL Post-Training Infrastructure
andersonbcdefg · x · 2026-08-22
Modal has released Training Gym, a Python SDK designed for reinforcement learning post-training on the Modal platform. It abstracts away infrastructure concerns such as cluster topology, Ray/NCCL bring-up, volume mounting, checkpointing, and serving for evaluation and rollouts.
Key Features:
- Quickstart: Supports Python 3.12 with installation via pip or uv.
- Configuration Example: Includes a full configuration example using Qwen34B and MathDataset, detailing parameters like GPU type, tensor parallelism, rollout batch size, and memory fractions.
- Observability: Built an observability system on top of slimeframework and radixark miles to address the critical need for robust monitoring in RL workflows.
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