Reinforcement Learning
stable-baselines3
TensorBoard
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use happycoding/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use happycoding/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="happycoding/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2cf81aa14512a90e2f02bfb23c67d92de0605e319165173ba20b97257a1f6892
- Size of remote file:
- 42.6 kB
- SHA256:
- 0762c60b8952f57601a85c2d5d3d6f6e862f4cc07ba530b06e3bd7b2d806a2a3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.