Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use robertou2/TEST2ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use robertou2/TEST2ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="robertou2/TEST2ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download ppo-aterrizaje-v2.zip from robertou2/TEST2ppo-LunarLander-v2: direct link, hf CLI and curl.
- Browser
- Download file 144 kB
-
https://huggingface.co/robertou2/TEST2ppo-LunarLander-v2/resolve/main/ppo-aterrizaje-v2.zip
- Command line
-
hf download hf://robertou2/TEST2ppo-LunarLander-v2/ppo-aterrizaje-v2.zip
-
curl -L -o ppo-aterrizaje-v2.zip https://huggingface.co/robertou2/TEST2ppo-LunarLander-v2/resolve/main/ppo-aterrizaje-v2.zip
144 kB
- Xet hash:
- f652425e220d829aef5b9e704e2e2b5646956ec19c1edcfd65d86f1adcf24595
- Size of remote file:
- 144 kB
- SHA256:
- 2205fcc79b511b6b7c5c8f6d0021b98741c1a078da0bfbee90b0df02c50a5561
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.