Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use jarguello76/reinforcement_learning_lunar_landing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use jarguello76/reinforcement_learning_lunar_landing with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="jarguello76/reinforcement_learning_lunar_landing", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd5426b1bcfd6535c4fc0b6a6079c3bc7f900dcc51bb1b9e5fad48d764c44df1
- Size of remote file:
- 147 kB
- SHA256:
- c08dfdc62af92d69544dc6c83a311b96af58170f613d9c23c1c99fc35a367c63
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.