Reinforcement Learning
stable-baselines3
deep-reinforcement-learning
fluidgym
active-flow-control
fluid-dynamics
simulation
RBC2D-hard-v0
Eval Results (legacy)
Instructions to use safe-autonomous-systems/ma-sac-RBC2D-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-sac-RBC2D-hard-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="safe-autonomous-systems/ma-sac-RBC2D-hard-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d4eec97514c3ca9133a375e3b5f062e4e1cc09f7782fd37c4af21471acc18ed
- Size of remote file:
- 15 MB
- SHA256:
- b769d4d29d617fa4b5c967286f3d14bdbf278ca8d761647ec73e3361074e26d9
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