Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Spydurp/SpaceInvaders with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Spydurp/SpaceInvaders with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Spydurp/SpaceInvaders", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e15fae3aee95126baeb1207dff4250d6132095339d850fbfab55dbf21ba9b2d3
- Size of remote file:
- 36.2 kB
- SHA256:
- 1f01d88bf85c841549543e11363cc53fc0479dede6a242ae526727c8b4b43260
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.