Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use vtorg/rl-course-unit-1-ppo-lunarlander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use vtorg/rl-course-unit-1-ppo-lunarlander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="vtorg/rl-course-unit-1-ppo-lunarlander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 062f46b
Update README.md
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README.md
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This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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## Usage (with Stable-baselines3)
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This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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## Usage (with Stable-baselines3)
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```
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model = PPO(
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policy = 'MlpPolicy',
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env = env,
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n_steps = 2048,
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batch_size = 512,
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n_epochs = 4,
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gamma = 0.099,
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gae_lambda = 0.98,
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ent_coef = 0.01,
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learning_rate=0.00001,
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verbose=1,
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tensorboard_log="./ppo_tensorboard/")
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model.learn(total_timesteps=int(10e6))
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```
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