Reinforcement Learning
stable-baselines3
ALE/SpaceInvaders-v5
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use aestoquera/ppo-SpaceInvaders-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use aestoquera/ppo-SpaceInvaders-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="aestoquera/ppo-SpaceInvaders-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
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Download README.md from aestoquera/ppo-SpaceInvaders-v4: direct link, hf CLI and curl.
- Browser
- Download file 811 Bytes
-
https://huggingface.co/aestoquera/ppo-SpaceInvaders-v4/resolve/main/README.md
- Command line
-
hf download hf://aestoquera/ppo-SpaceInvaders-v4/README.md
-
curl -L -o README.md https://huggingface.co/aestoquera/ppo-SpaceInvaders-v4/resolve/main/README.md
811 Bytes
metadata
library_name: stable-baselines3
tags:
- ALE/SpaceInvaders-v5
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: ALE/SpaceInvaders-v5
type: ALE/SpaceInvaders-v5
metrics:
- type: mean_reward
value: 4.30 +/- 1.79
name: mean_reward
verified: false
PPO Agent playing ALE/SpaceInvaders-v5
This is a trained model of a PPO agent playing ALE/SpaceInvaders-v5 using the stable-baselines3 library.
Usage (with Stable-baselines3)
TODO: Add your code
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...