Instructions to use Addwater/rl-course with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Addwater/rl-course with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Addwater/rl-course", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - Taxi-v3 | |
| - q-learning | |
| - reinforcement-learning | |
| - custom-implementation | |
| model-index: | |
| - name: rl-course | |
| results: | |
| - task: | |
| type: reinforcement-learning | |
| name: reinforcement-learning | |
| dataset: | |
| name: Taxi-v3 | |
| type: Taxi-v3 | |
| metrics: | |
| - type: mean_reward | |
| value: 7.54 +/- 2.73 | |
| name: mean_reward | |
| verified: false | |
| # **PPO** Agent playing **LunarLander-v2** | |
| This is a trained model of a **PPO** agent playing **LunarLander-v2** | |
| using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). | |
| ## Usage (with Stable-baselines3) | |
| TODO: Add your code | |
| ```python | |
| from stable_baselines3 import ... | |
| from huggingface_sb3 import load_from_hub | |
| ... | |
| ``` | |