Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use ThomasSimonini/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use ThomasSimonini/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="ThomasSimonini/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download a2c-PandaReachDense-v3.zip from ThomasSimonini/a2c-PandaReachDense-v3: direct link, hf CLI and curl.
- Browser
- Download file 107 kB
-
https://huggingface.co/ThomasSimonini/a2c-PandaReachDense-v3/resolve/main/a2c-PandaReachDense-v3.zip
- Command line
-
hf download hf://ThomasSimonini/a2c-PandaReachDense-v3/a2c-PandaReachDense-v3.zip
-
curl -L -o a2c-PandaReachDense-v3.zip https://huggingface.co/ThomasSimonini/a2c-PandaReachDense-v3/resolve/main/a2c-PandaReachDense-v3.zip
107 kB
- Xet hash:
- 2b288a68695e6b7e3218b6b86502110a990cc7cb37a3554f8f74ca81d735f340
- Size of remote file:
- 107 kB
- SHA256:
- 30d38891845e2ed061d1aed4e9ea4da19752eb3c01cd482d4ad1f448000c0c67
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.