Reinforcement Learning
stable-baselines3
Reacher-v5
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use farama-minari/Reacher-v5-SAC-simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use farama-minari/Reacher-v5-SAC-simple with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="farama-minari/Reacher-v5-SAC-simple", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 592fb58231013cf28df0490e98f5ba969185060da1b79e63faa7f1bf2bafca37
- Size of remote file:
- 3.11 MB
- SHA256:
- 09caa6074d373611d8cbf96f517fb362a598cc0dc14e2fc0494b5c35db536b5f
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