Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use baronase/unit3-atari-dqn-1m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use baronase/unit3-atari-dqn-1m with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="baronase/unit3-atari-dqn-1m", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download results.json from baronase/unit3-atari-dqn-1m: direct link, hf CLI and curl.
- Browser
- Download file 153 Bytes
-
https://huggingface.co/baronase/unit3-atari-dqn-1m/resolve/main/results.json
- Command line
-
hf download hf://baronase/unit3-atari-dqn-1m/results.json
-
curl -L -o results.json https://huggingface.co/baronase/unit3-atari-dqn-1m/resolve/main/results.json
153 Bytes
| {"mean_reward": 538.0, "std_reward": 149.55266630856167, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2025-01-28T09:39:55.488911"} |