Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Abhinay45/SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Abhinay45/SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Abhinay45/SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from Abhinay45/SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 36.2 kB
-
https://huggingface.co/Abhinay45/SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://Abhinay45/SpaceInvadersNoFrameskip-v4/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/Abhinay45/SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
36.2 kB
- Xet hash:
- 55d71fbb4d5a403ad7c47f32715d1fca0d06bdb4678c0bc138b94a60acc51c3d
- Size of remote file:
- 36.2 kB
- SHA256:
- e1a36e863cda0dba8a65dfd906fae35c1053c70ddeb4661bb9a3cf95f995483c
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