Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use AtilliO/a2c-PandaReachDense-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use AtilliO/a2c-PandaReachDense-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="AtilliO/a2c-PandaReachDense-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from AtilliO/a2c-PandaReachDense-v2: direct link, hf CLI and curl.
- Browser
- Download file 2.39 kB
-
https://huggingface.co/AtilliO/a2c-PandaReachDense-v2/resolve/refs%2Fpr%2F1/vec_normalize.pkl
- Command line
-
hf download hf://AtilliO/a2c-PandaReachDense-v2@refs/pr/1/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/AtilliO/a2c-PandaReachDense-v2/resolve/refs%2Fpr%2F1/vec_normalize.pkl
2.39 kB
- Xet hash:
- 68a71c5b53e241fbc3b98e10002647abaab1858c3564dc31a8a500f0d307f0e8
- Size of remote file:
- 2.39 kB
- SHA256:
- 18e215e7d446321bd560e12fd381d2f5caf1163ef4b88292a334b2b7d409edd3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.