Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Developer-Karthi/dqn-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Developer-Karthi/dqn-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Developer-Karthi/dqn-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from Developer-Karthi/dqn-SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 32.8 kB
-
https://huggingface.co/Developer-Karthi/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://Developer-Karthi/dqn-SpaceInvadersNoFrameskip-v4/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/Developer-Karthi/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
32.8 kB
- Xet hash:
- f3739fc77c8c71914881c1ebf6180fb6356aba9ce7f3515af3f6a765f0e6f712
- Size of remote file:
- 32.8 kB
- SHA256:
- 037fd2505ac7a977c0b7d8348e1591992c7b346425f8125e254fdd6db8e8fdb7
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