Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Freddthink/DQN-SpaceInvadersNoFrameskip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Freddthink/DQN-SpaceInvadersNoFrameskip with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Freddthink/DQN-SpaceInvadersNoFrameskip", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from Freddthink/DQN-SpaceInvadersNoFrameskip: direct link, hf CLI and curl.
- Browser
- Download file 37.3 kB
-
https://huggingface.co/Freddthink/DQN-SpaceInvadersNoFrameskip/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://Freddthink/DQN-SpaceInvadersNoFrameskip/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/Freddthink/DQN-SpaceInvadersNoFrameskip/resolve/main/train_eval_metrics.zip
37.3 kB
- Xet hash:
- a8114b3c58e4538fa4aa53adea1a670f3a7e775d56ad1023affa59ea06a0d494
- Size of remote file:
- 37.3 kB
- SHA256:
- f41e861a37d0f4d97ad59c51f27643622971b4ee160f92e2db06ccc99234332c
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