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PPO-lunarlanderv2-hfRLU1
thatgeeman/PPO-lunarlanderv2-hfRLU1
PPO-lunarlanderv2-hfRLU1 is a reinforcement learning model from thatgeeman. 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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.mp4187 KB · 38%
At a glance
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Access
- Public
- Created
- Mar 6, 2023
- Updated
- Mar 8, 2023
- SHA
- 03ec7951
Model card
From the Hugging Face model README
PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
Model parameters
model = PPO(
policy = 'MlpPolicy',
env = env,
n_steps = 1024,
batch_size = 64,
n_epochs = 10,
gamma = 0.999,
gae_lambda = 0.98,
ent_coef = 0.01,
verbose=1)
Trained for 10^6 steps using
steps = 1e6
model.learn(total_timesteps=int(steps))
Usage (with Stable-baselines3)
TODO: Add your code
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Created
- Mar 6, 2023
- Updated
- Mar 8, 2023