Integrations
Huggingface Hub Integration
List and videos of trained agents can be found on our Huggingface page: https://huggingface.co/sb3
Upload model to hub (same syntax as for enjoy.py
):
python -m rl_zoo3.push_to_hub --algo ppo --env CartPole-v1 -f logs/ -orga sb3 -m "Initial commit"
you can choose custom repo-name
(default: {algo}-{env_id}
) by
passing a --repo-name
argument.
Download model from hub:
python -m rl_zoo3.load_from_hub --algo ppo --env CartPole-v1 -f logs/ -orga sb3
Experiment tracking
We support tracking experiment data such as learning curves and hyperparameters via Weights and Biases.
The following command
python train.py --algo ppo --env CartPole-v1 --track --wandb-project-name sb3
yields a tracked experiment at this URL.
To add a tag to the run, (e.g. optimized
), use the argument
--wandb-tags optimized
.