Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use LucasBlock/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use LucasBlock/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="LucasBlock/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download a2c-PandaReachDense-v3.zip from LucasBlock/a2c-PandaReachDense-v3: direct link, hf CLI and curl.
- Browser
- Download file 114 kB
-
https://huggingface.co/LucasBlock/a2c-PandaReachDense-v3/resolve/main/a2c-PandaReachDense-v3.zip
- Command line
-
hf download hf://LucasBlock/a2c-PandaReachDense-v3/a2c-PandaReachDense-v3.zip
-
curl -L -o a2c-PandaReachDense-v3.zip https://huggingface.co/LucasBlock/a2c-PandaReachDense-v3/resolve/main/a2c-PandaReachDense-v3.zip
114 kB
- Xet hash:
- 24d6bec40a9fa56a93ffd4d5599f71a3d532f2cc19ab97bafa54e64c880c204b
- Size of remote file:
- 114 kB
- SHA256:
- eeb5fbbd35806a6e632eee2a46b58806ab942d54790e61887f377972c7c826bc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.