Reinforcement Learning
stable-baselines3
deep-reinforcement-learning
fluidgym
active-flow-control
fluid-dynamics
simulation
RBC3D-hard-v0
Eval Results (legacy)
Instructions to use safe-autonomous-systems/ma-ppo-RBC3D-hard-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-hard-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="safe-autonomous-systems/ma-ppo-RBC3D-hard-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eaa96db6340a3cee7ac9813777243a0c589a0a4e9b5c51592c61aedb6a9133b9
- Size of remote file:
- 18.8 MB
- SHA256:
- 2e12a9b2047c95fc56a93e848cc67249c6fffc2dfd61dad174d4422bd957fa4f
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