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97jmlr
/
dqn-SapaceInv

Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use 97jmlr/dqn-SapaceInv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • stable-baselines3

    How to use 97jmlr/dqn-SapaceInv with stable-baselines3:

    from huggingface_sb3 import load_from_hub
    checkpoint = load_from_hub(
    	repo_id="97jmlr/dqn-SapaceInv",
    	filename="{MODEL FILENAME}.zip",
    )
  • Notebooks
  • Google Colab
  • Kaggle
dqn-SapaceInv
54.7 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
97jmlr's picture
97jmlr
Initial commit
90e63a8 almost 3 years ago
  • dqn-SpaceInvadersNoFrameskip-v4
    Initial commit almost 3 years ago
  • .gitattributes
    1.56 kB
    Initial commit almost 3 years ago
  • README.md
    2.75 kB
    Initial commit almost 3 years ago
  • args.yml
    1.21 kB
    Initial commit almost 3 years ago
  • config.yml
    549 Bytes
    Initial commit almost 3 years ago
  • dqn-SpaceInvadersNoFrameskip-v4.zip
    27.2 MB
    xet
    Initial commit almost 3 years ago
  • env_kwargs.yml
    23 Bytes
    Initial commit almost 3 years ago
  • replay.mp4
    202 kB
    xet
    Initial commit almost 3 years ago
  • results.json
    153 Bytes
    Initial commit almost 3 years ago
  • train_eval_metrics.zip
    35.4 kB
    xet
    Initial commit almost 3 years ago