Reinforcement Learning
stable-baselines3
deep-reinforcement-learning
fluidgym
active-flow-control
fluid-dynamics
simulation
RBC3D-easy-v0
Eval Results (legacy)
Instructions to use safe-autonomous-systems/ma-ppo-RBC3D-easy-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use safe-autonomous-systems/ma-ppo-RBC3D-easy-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="safe-autonomous-systems/ma-ppo-RBC3D-easy-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e9fa8301478379333b687039c8fa0307e24c0531e49332c5aaa2c5e578b960c
- Size of remote file:
- 8.84 MB
- SHA256:
- 2094613575a76ccd8cb0f352cf607e98238c83b335b0a8b56c8254a2c8e6d0fe
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