Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-rl-course
Eval Results (legacy)
Instructions to use Rivershen/rl-class-spaceinvaders-dqn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Rivershen/rl-class-spaceinvaders-dqn with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Rivershen/rl-class-spaceinvaders-dqn", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
rl-class-spaceinvaders-dqn
This is a trained Reinforcement Learning model for the Hugging Face Deep Reinforcement Learning Course (Unit 3).
- Environment:
SpaceInvadersNoFrameskip-v4 - Library:
stable-baselines3 - Performance: Mean Reward =
650.0 +/- 45.0 - Description: Deep RL Course Unit 3 - Deep Q-Learning (DQN) playing SpaceInvaders
- Downloads last month
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Evaluation results
- mean_reward on SpaceInvadersNoFrameskip-v4self-reported650.0 +/- 45.0