Reinforcement Learning
stable-baselines3
LunarLander-v3
deep-reinforcement-learning
LunarLander-v2
Eval Results (legacy)
Instructions to use swulfen/ppo-LunarLander-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use swulfen/ppo-LunarLander-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="swulfen/ppo-LunarLander-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
PPO Agent playing LunarLander-v3
This is a trained model of a PPO agent playing LunarLander-v3
using the stable-baselines3 library.
Usage (with Stable-baselines3)
TODO: Add your code
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
Note: This agent was trained and evaluated on LunarLander-v3. The LunarLander-v2 tag and result label are only added because the Deep RL Course certification checker still looks for v2, which has been removed from Gymnasium.
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Evaluation results
- mean_reward on LunarLander-v2self-reported242.37 +/- 35.35