Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use jcms-bits/Deep_RL_Course with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use jcms-bits/Deep_RL_Course with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="jcms-bits/Deep_RL_Course", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28e28487c8ce37e9404896429847e7028bd0ddb88cab8a75003e7ffe92cd6b2b
- Size of remote file:
- 148 kB
- SHA256:
- eafddb557201efe4bc4fad118e71948668a4d3f9835e348eccd0d70c9befb702
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.