README.md

metadata

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: 262.89 +/- 16.52
            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.

Usage (with Stable-baselines3)

from stable_baselines3 import PPO
from huggingface_sb3 import load_from_hub
from stable_baselines3.common.vec_env import DummyVecEnv
from stable_baselines3.common.env_util import make_vec_env
import gymnasium as gym

# Load the model from the Hub
checkpoint = load_from_hub(
    repo_id="HamzaChera/ppo-LunarLander-v2",
    filename="ppo-LunarLander-v2.zip",
)

model = PPO.load(checkpoint)

# Create the environment
env = make_vec_env("LunarLander-v2", n_envs=1)

obs = env.reset()
while True:
    action, _states = model.predict(obs, deterministic=True)
    obs, rewards, dones, info = env.step(action)
    env.render()
...