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innocent-charles/RL-ppo-LunarLander-v2
RL-ppo-LunarLander-v2 is a reinforcement learning model from innocent-charles. 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 model is trained using PPO [proximal policy optimization algorithm invented by OpenAI] The RL-based agent playing to land correctly on the moon using LunarLander environment as simulator.
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From the Hugging Face model README
This model is trained using PPO [proximal policy optimization algorithm invented by OpenAI] The RL-based agent playing to land correctly on the moon using LunarLander environment as simulator.
TODO: Add your code
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
repo_id = "innocent-charles/RL-ppo-LunarLander-v2"
filename = "RL-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)
...