Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use swaroop06/dqn-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use swaroop06/dqn-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="swaroop06/dqn-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
DQN agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of an DQN agent playing SpaceInvadersNoFrameskip-v4 for the Hugging Face Deep Reinforcement Learning Course (Unit 3).
Evaluation Results
- Mean Reward: 650.00 +/- 120.00
- Environment: SpaceInvadersNoFrameskip-v4
- Algorithm: DQN
- Library: stable-baselines3
Usage
Trained and evaluated for the Hugging Face Deep RL Course certification.
- Downloads last month
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Evaluation results
- mean_reward on SpaceInvadersNoFrameskip-v4self-reported650.00 +/- 120.00