Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use jayeshgar/dqn-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use jayeshgar/dqn-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="jayeshgar/dqn-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from jayeshgar/dqn-SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 37.4 kB
-
https://huggingface.co/jayeshgar/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://jayeshgar/dqn-SpaceInvadersNoFrameskip-v4/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/jayeshgar/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
37.4 kB
- Xet hash:
- e55c253482a6d791f5cb89aeaf1b821363dbed209cbc942c07dedcd454049310
- Size of remote file:
- 37.4 kB
- SHA256:
- 3db7656b4902e541c1bcf04e933476dd7482a99492154b65e4cb063a81f6714d
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