Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use tmoroder/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use tmoroder/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="tmoroder/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44cf74fc3a90723d0d0cea1c190824d0e693d9eb936f4f6aea9497d35fb30cd0
- Size of remote file:
- 148 kB
- SHA256:
- 23eb7f3cf0cd5241fb309bdf44c31e2e016b0c78e5005edd099905e63bdee084
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.