Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use TAS-Theo/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use TAS-Theo/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="TAS-Theo/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from TAS-Theo/a2c-PandaReachDense-v3: direct link, hf CLI and curl.
- Browser
- Download file 2.66 kB
-
https://huggingface.co/TAS-Theo/a2c-PandaReachDense-v3/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://TAS-Theo/a2c-PandaReachDense-v3/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/TAS-Theo/a2c-PandaReachDense-v3/resolve/main/vec_normalize.pkl
2.66 kB
- Xet hash:
- ffac617996727a797eb58bdb97e11fc16de66b0ffc8fa6d80af28d7fc9c7041b
- Size of remote file:
- 2.66 kB
- SHA256:
- 7b7feaa09fd755a4b646d76670f1a85d3d07ca9e903b8082432edbb333e2b49d
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