Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use SakataHalmi/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use SakataHalmi/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="SakataHalmi/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from SakataHalmi/a2c-PandaReachDense-v3: direct link, hf CLI and curl.
- Browser
- Download file 3.08 kB
-
https://huggingface.co/SakataHalmi/a2c-PandaReachDense-v3/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://SakataHalmi/a2c-PandaReachDense-v3/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/SakataHalmi/a2c-PandaReachDense-v3/resolve/main/vec_normalize.pkl
3.08 kB
- Xet hash:
- 2793f758581e1a2efd9236deb0aa6e88b09a9ebe41c3db3dfcb3cd194c52aef0
- Size of remote file:
- 3.08 kB
- SHA256:
- ebedeeabd7112c88eefdfe2eafd03892ac7ecac2176b9549d69d4147b0974c0b
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