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:
- 6006b54479de029d28a32a9d8480ca63b9d9c0b43a7223471c8b2a3c53ac0d4f
- Size of remote file:
- 273 kB
- SHA256:
- 01175b9038d3473ccd2dc38309da13f48361b9b433c31c57ae9808c5ef6d2dcd
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