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quant-sheep/ppo-LunarLander-v2
ppo-LunarLander-v2 is a reinforcement learning model from quant-sheep. 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. The card lists the license as mit.
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 huggingface_sb3 import load_from_hub
repo_id = "zhiweiyoung/ppo-LunarLander-v2" # The repo_id
filename = "zhiwei_ppo.zip" # The model filename.zip
# When the model was trained on Python 3.8 the pickle protocol is 5
# But Python 3.6, 3.7 use protocol 4
# In order to get compatibility we need to:
# 1. Install pickle5 (we done it at the beginning of the colab)
# 2. Create a custom empty object we pass as parameter to PPO.load()
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)