Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use AdonaiHS/atari-game-Space-Invaders with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use AdonaiHS/atari-game-Space-Invaders with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="AdonaiHS/atari-game-Space-Invaders", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download results.json from AdonaiHS/atari-game-Space-Invaders: direct link, hf CLI and curl.
- Browser
- Download file 152 Bytes
-
https://huggingface.co/AdonaiHS/atari-game-Space-Invaders/resolve/main/results.json
- Command line
-
hf download hf://AdonaiHS/atari-game-Space-Invaders/results.json
-
curl -L -o results.json https://huggingface.co/AdonaiHS/atari-game-Space-Invaders/resolve/main/results.json
152 Bytes
| {"mean_reward": 587.5, "std_reward": 92.12084454671484, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2023-02-15T20:05:33.207600"} |