Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Fhermin/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Fhermin/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Fhermin/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download a2c-PandaReachDense-v3.zip from Fhermin/a2c-PandaReachDense-v3: direct link, hf CLI and curl.
- Browser
- Download file 110 kB
-
https://huggingface.co/Fhermin/a2c-PandaReachDense-v3/resolve/main/a2c-PandaReachDense-v3.zip
- Command line
-
hf download hf://Fhermin/a2c-PandaReachDense-v3/a2c-PandaReachDense-v3.zip
-
curl -L -o a2c-PandaReachDense-v3.zip https://huggingface.co/Fhermin/a2c-PandaReachDense-v3/resolve/main/a2c-PandaReachDense-v3.zip
110 kB
- Xet hash:
- 841c044b2c2ab48813a6aee930913d566d6ecef0581d943121e86f803f4af1e0
- Size of remote file:
- 110 kB
- SHA256:
- 9edcf076b874981e4062aeec03fc89ef1ae5a6a394cf8ff59507fc2349f051cb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.