Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Karthik32/dqn-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Karthik32/dqn-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Karthik32/dqn-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
DQN Agent playing SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4 using stable-baselines3. Trained for Unit 3 of the Hugging Face Deep Reinforcement Learning Course.
Evaluation Results
- Mean Reward: 580.00 +/- 110.00 (min requirement: 200)
- Downloads last month
- 13
Evaluation results
- mean_reward on SpaceInvadersNoFrameskip-v4self-reported580.00 +/- 110.00