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LunarLander-v2-PPO
davidhornshaw/LunarLander-v2-PPO
LunarLander-v2-PPO is a reinforcement learning model from davidhornshaw. 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
- Feb 27, 2025
- Updated
- Feb 27, 2025
- SHA
- 9a0bcf35
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)
from stable_baselines3 import PPO
from huggingface_sb3 import load_from_hub
# repo info
checkpoint = load_from_hub(
repo_id="davidhornshaw/LunarLander-v2-PPO",
filename="ppo-LunarLander-v2.zip"
)
# make model
checkpoint = load_from_hub(repo_id, filename)
model = PPO.load(checkpoint, custom_objects=custom_objects, print_system_info=True)
# evaluate model
eval_env = Monitor(gym.make("LunarLander-v2", render_mode='rgb_array'))
mean_reward, std_reward = evaluate_policy(model, eval_env, n_eval_episodes=100, deterministic=True)
print(f"mean_reward={mean_reward:.2f} +/- {std_reward}")
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Created
- Feb 27, 2025
- Updated
- Feb 27, 2025