Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use vjkrish/spaceInvadersNoFramesSkip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use vjkrish/spaceInvadersNoFramesSkip with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="vjkrish/spaceInvadersNoFramesSkip", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from vjkrish/spaceInvadersNoFramesSkip: direct link, hf CLI and curl.
- Browser
- Download file 37.1 kB
-
https://huggingface.co/vjkrish/spaceInvadersNoFramesSkip/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://vjkrish/spaceInvadersNoFramesSkip/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/vjkrish/spaceInvadersNoFramesSkip/resolve/main/train_eval_metrics.zip
37.1 kB
- Xet hash:
- 25e00a7d7b161f6558d7a1ab710c40b04f269c69104d4a01dcc04ea3883d4dec
- Size of remote file:
- 37.1 kB
- SHA256:
- 59f7597524446503a4e7756b4ec6a36cecc379a1b7fa3e4cec1d30d71d94633e
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