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potello/ppo-LunarLander-v2
ppo-LunarLander-v2 is a reinforcement learning model from potello. 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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From the Hugging Face model README
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
from stable_baselines3 import PPO
from stable_baselines3.common.monitor import Monitor
from huggingface_sb3 import load_from_hub
repo_id = "potello/ppo-LunarLander-v2"
filename = "ppo-LunarLander-v2.zip"
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)
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}")