Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
dqn
deep-rl-course
Eval Results (legacy)
Instructions to use rohit0128/dqn-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use rohit0128/dqn-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="rohit0128/dqn-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
dqn-SpaceInvadersNoFrameskip-v4
This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4. This model was trained as part of the Hugging Face Deep Reinforcement Learning Course.
Evaluation Results
- Environment:
SpaceInvadersNoFrameskip-v4 - Algorithm:
DQN - Library:
stable-baselines3 - Mean Reward:
580.00 +/- 30.00
Usage
To evaluate this model locally or play with it, download the model files from this repository.
- Downloads last month
- 4
Evaluation results
- mean_reward on SpaceInvadersNoFrameskip-v4self-reported580.00 +/- 30.00