(integrations)=

# Integrations

## Huggingface Hub Integration

Lists 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](https://wandb.ai).

The following command

```
python train.py --algo ppo --env CartPole-v1 --track --wandb-project-name sb3
```

yields a tracked experiment at this
[URL](https://wandb.ai/openrlbenchmark/sb3/runs/1b65ldmh).

To add a tag to the run (e.g. `optimized`), use the argument
`--wandb-tags optimized`.