Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use heesup/dqn-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use heesup/dqn-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="heesup/dqn-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from heesup/dqn-SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 37 kB
-
https://huggingface.co/heesup/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://heesup/dqn-SpaceInvadersNoFrameskip-v4/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/heesup/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
37 kB
- Xet hash:
- b4e2a97a69bc03f4052cc1d4fc7a6dd195ac21631377b36bd903a48dc58d6bc2
- Size of remote file:
- 37 kB
- SHA256:
- 7106e74ea01104914422d0a055f137ad370c42c6a9fb7942ef2c638fef2c27b9
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