Tier 2 · NVIDIA GPUs
Train a policy
Training runs in mjlab on MuJoCo Warp, thousands of environments on one GPU. It needs CUDA, so it cannot run in this tab. This page writes the job; you run it, or send it to us.
- Robots, train open
- 48
- With stock mjlab task
- 1
Velocity-tracking reward on a flat plane. Stock env samples forward, lateral and yaw commands and randomises friction and pushes.
Run it yourself · mjlab
# NVIDIA GPU + CUDA required (mjlab runs on MuJoCo Warp). Does not run in a browser.
git clone https://github.com/mujocolab/mjlab.git && cd mjlab
uv run train Mjlab-Velocity-Flat-Unitree-G1 \
--env.scene.num-envs 4096 \
--agent.max-iterations 3000
# watch a checkpoint afterwards
uv run play Mjlab-Velocity-Flat-Unitree-G1 --checkpoint-file logs/rsl_rl/<run>/model_<iter>.pt