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ppo-LunarLander-v2
mrj22/ppo-LunarLander-v2
ppo-LunarLander-v2 is a reinforcement learning model from mrj22. 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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At a glance
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Access
- Public
- Created
- Aug 16, 2023
- Updated
- Aug 16, 2023
- SHA
- b0c95187
Model card
From the Hugging Face model README
Wooooohhoooo value: 263.21 +/- 18.25**
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)
This is the standard PPO model model = PPO( policy = 'MlpPolicy', env = env, n_steps = 1024, batch_size = 64, n_epochs = 4, gamma = 0.999, gae_lambda = 0.98, ent_coef = 0.01, verbose=1)
Train it for 1,000,000 timesteps
model.learn(total_timesteps=1000000)
Save the model
model_name = "ppo-LunarLander-v2" model.save(model_name)
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Created
- Aug 16, 2023
- Updated
- Aug 16, 2023