Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use boro/dqn-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use boro/dqn-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="boro/dqn-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from boro/dqn-SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 31 kB
-
https://huggingface.co/boro/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://boro/dqn-SpaceInvadersNoFrameskip-v4/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/boro/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
31 kB
- Xet hash:
- 7bfa35627d17829e2aeced74e4419aaac27c239d61a1f4c50680a1d1d0a7f330
- Size of remote file:
- 31 kB
- SHA256:
- 90aaaebb0cfe775496252bbe64e594b171cf8233f6c5bff71ada9cdad6dcfa18
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