Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
ppo
deep-rl-course
custom-implementation
Eval Results (legacy)
Instructions to use Deepuamrita23115/ppo-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Deepuamrita23115/ppo-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Deepuamrita23115/ppo-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
ppo-SpaceInvadersNoFrameskip-v4
This model was trained as part of the Hugging Face Deep Reinforcement Learning Course.
Model Description
- Environment:
SpaceInvadersNoFrameskip-v4 - Library:
stable-baselines3 - Algorithm:
ppo - Mean Reward:
300.00 +/- 20.00
Evaluation Results
The model was evaluated on SpaceInvadersNoFrameskip-v4 and achieved an average reward of 300.00 with a standard deviation of 20.00.
- Downloads last month
- 6
Evaluation results
- mean_reward on SpaceInvadersNoFrameskip-v4self-reported300.00 +/- 20.00