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hf-LunarLander-1-ppo
Laz4rz/hf-LunarLander-1-ppo
hf-LunarLander-1-ppo is a reinforcement learning model from Laz4rz. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for stable-baselines3.
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
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At a glance
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Access
- Public
- Created
- Apr 26, 2024
- Updated
- Apr 26, 2024
- SHA
- 9d0e52f7
Model card
From the Hugging Face model README
PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
Usage (with Stable-baselines3)
Follow to eval the agent locally:
repo_id = "Laz4rz/hf-LunarLander-1-ppo" # The repo_id
filename = "ppo-LunarLander-v2.zip" # The model filename.zip
checkpoint = load_from_hub(repo_id, filename)
model = PPO.load(checkpoint)
eval_env = Monitor(gym.make("LunarLander-v2"))
mean_reward, std_reward = evaluate_policy(model, eval_env, n_eval_episodes=10, deterministic=True)
print(f"mean_reward={mean_reward:.2f} +/- {std_reward}")
...
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Created
- Apr 26, 2024
- Updated
- Apr 26, 2024