Downloads · 30 days
0
0% of all-time downloads
dmenini/ppo-LunarLander-v2
ppo-LunarLander-v2 is a reinforcement learning model from dmenini. 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.
Downloads · 30 days
0
0% of all-time downloads
All-time downloads
23
Public
Repo size
559 KB
Likes
0
Public
Click a slice to open those files.
.mp4202 KB · 39%
From the Hugging Face model README
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
import gym
from stable_baselines3 import PPO
from huggingface_sb3 import load_from_hub
checkpoint = load_from_hub(
repo_id="dmenini/ppo-LunarLander-v2",
filename="ppo-LunarLander-v2.zip"
)
model = PPO.load(checkpoint)
env = gym.make("LunarLander-v2")
# Evaluate the agent and watch it
eval_env = gym.make("LunarLander-v2")
mean_reward, std_reward = evaluate_policy(
model, eval_env, render=True, n_eval_episodes=5, deterministic=True, warn=False
)
print(f"mean_reward={mean_reward:.2f} +/- {std_reward}")