readme: ---
  library_name: stable-baselines3
  tags:
  - LunarLander-v2
  - deep-reinforcement-learning
  - reinforcement-learning
  - stable-baselines3
  model-index:
  - name: PPO
    results:
    - task:
        type: reinforcement-learning
        name: reinforcement-learning
      dataset:
        name: LunarLander-v2
        type: LunarLander-v2
      metrics:
      - type: mean_reward
        value: 273.37 +/- 24.38
        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 huggingface_sb3 import load_from_hub
  repo_id = "BlackNoodle/ppo-LunarLander-v2" # The repo_id
  filename = "ppo-LunarLander-v2.zip" # The model filename.zip
  
  # When the model was trained on Python 3.8 the pickle protocol is 5
  # But Python 3.6, 3.7 use protocol 4
  # In order to get compatibility we need to:
  # 1. Install pickle5 (we done it at the beginning of the colab)
  # 2. Create a custom empty object we pass as parameter to PPO.load()
  custom_objects = {
              "learning_rate": 0.0,
              "lr_schedule": lambda _: 0.0,
              "clip_range": lambda _: 0.0,
  }
  
  checkpoint = load_from_hub(repo_id, filename)
  model = PPO.load(checkpoint, custom_objects=custom_objects, print_system_info=True)
  
  ```
  