Reinforcement Learning
Transformers
TensorBoard
LunarLander-v2
ppo
deep-reinforcement-learning
custom-implementation
deep-rl-course
Eval Results (legacy)
Instructions to use rishipatel92/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rishipatel92/ppo-LunarLander-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rishipatel92/ppo-LunarLander-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - LunarLander-v2 | |
| - ppo | |
| - deep-reinforcement-learning | |
| - reinforcement-learning | |
| - custom-implementation | |
| - deep-rl-course | |
| model-index: | |
| - name: PPO | |
| results: | |
| - task: | |
| type: reinforcement-learning | |
| name: reinforcement-learning | |
| dataset: | |
| name: LunarLander-v2 | |
| type: LunarLander-v2 | |
| metrics: | |
| - type: mean_reward | |
| value: -228.76 +/- 140.11 | |
| name: mean_reward | |
| verified: false | |
| # PPO Agent Playing LunarLander-v2 | |
| This is a trained model of a PPO agent playing LunarLander-v2. | |
| # Hyperparameters | |