Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use zypchn/a2c-Lunar-Lander with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use zypchn/a2c-Lunar-Lander with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="zypchn/a2c-Lunar-Lander", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
A2C Agent playing LunarLander-v2
This is a trained model of a A2C agent playing LunarLander-v2 using the stable-baselines3 library.
Usage (with Stable-baselines3)
TODO: Add your code
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
- Downloads last month
- -
Evaluation results
- mean_reward on LunarLander-v2self-reported47.81 +/- 135.90