Use the Stable-Baselines3 documentation and implement code to solve the CartPole environment with the Advantage Actor-Critic (A2C) algorithm.
Use the [Stable-Baselines3 documentation](https://stable-baselines3.readthedocs.io/en/master/) to implement the code to solve the CartPole environment with the Advantage Actor-Critic (A2C) algorithm.
> 🛠 **To be handed in**
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@@ -112,7 +112,7 @@ pip install huggingface_sb3
#### Upload the model on the Hub
Follow the Hugging Face Hub documentation to upload the previously learned model to the Hub.
Follow the [Hugging Face Hub documentation](https://huggingface.co/docs/hub/index) to upload the previously learned model to the Hub.
> 🛠 **To be handed in**
> Link the trained model in the `README.md` file.
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@@ -130,7 +130,7 @@ Weights & Biases (W&B) is a tool for machine learning experiment management. Wit
pip install wandb
```
Use the documentation of Stable-Baselines3 and Weights & Biases to track the CartPole training. Make the run public.
Use the documentation of Stable-Baselines3 and [Weights & Biases](https://docs.wandb.ai) to track the CartPole training. Make the run public.
🛠 Share the link of the wandb run in the `README.md` file.
