Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use RegisGraptin/a2c-PandaReachDense-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use RegisGraptin/a2c-PandaReachDense-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="RegisGraptin/a2c-PandaReachDense-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from RegisGraptin/a2c-PandaReachDense-v2: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/RegisGraptin/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://RegisGraptin/a2c-PandaReachDense-v2/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/RegisGraptin/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
3.06 kB
- Xet hash:
- b496ded5a1be9ee0b3bb386834463535083fa9e7dc263e82bd601ef636d4edcf
- Size of remote file:
- 3.06 kB
- SHA256:
- 60a7b8ec5f641ad88731f21e12d66da8b01d03a0374eb915d049116c93e0d890
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