Reinforcement Learning
stable-baselines3
ALE/Tetris-v5
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use haiphong0132/A2CTEST-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use haiphong0132/A2CTEST-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="haiphong0132/A2CTEST-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
A2C Agent playing ALE/Tetris-v5
This is a trained model of a A2C agent playing ALE/Tetris-v5 using the stable-baselines3 library.
Usage (with Stable-baselines3)
TODO: Add your code
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
- Downloads last month
- -
Evaluation results
- mean_reward on ALE/Tetris-v5self-reported0.00 +/- 0.00
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="haiphong0132/A2CTEST-v2", filename="{MODEL FILENAME}.zip", )