Train a Coding Agent in One Command: HF Unveils Remote Sandbox RL Solution
SergioPaniego · x · 2026-08-12
Hugging Face published a detailed tutorial on training real coding agents using TRL and OpenEnv with the OpenCode harness inside HF Jobs remote sandboxes.
Key highlights of this approach:
- Loop-owning mechanism: Unlike traditional RL training where the trainer drives the loop, this method lets the agent harness run its own loop, and the trainer learns directly from the exact tokens produced.
- Architecture agnostic: Although it uses OpenCode as the concrete agent, the architecture works for any agent running in a sandbox that communicates via an OpenAI-compatible API.
- Scalable rollouts: By using HF Jobs, every rollout runs in its own remote sandbox, scaling out beyond a single node. A single-command launcher is provided for easy reproduction.
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