Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use ramathuzen/dqn_atari_unit_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use ramathuzen/dqn_atari_unit_3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="ramathuzen/dqn_atari_unit_3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a7ec3c956067568f344d06f61c74cdec8a5dfac716d65b0e1b96b56f2a17005
- Size of remote file:
- 35.8 kB
- SHA256:
- 9152bbd521e14fee2865ec42d5fdfe35b8d06945930d42560aa6babfa5f96e90
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