Reinforcement Learning
stable-baselines3
PandaPickAndPlace-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use tmoroder/a2c-PandaPickAndPlace-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use tmoroder/a2c-PandaPickAndPlace-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="tmoroder/a2c-PandaPickAndPlace-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from tmoroder/a2c-PandaPickAndPlace-v3: direct link, hf CLI and curl.
- Browser
- Download file 3.04 kB
-
https://huggingface.co/tmoroder/a2c-PandaPickAndPlace-v3/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://tmoroder/a2c-PandaPickAndPlace-v3/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/tmoroder/a2c-PandaPickAndPlace-v3/resolve/main/vec_normalize.pkl
3.04 kB
- Xet hash:
- 6b711fd8111ed1b7c6759ce86fe142d8be2ebb83a70eff4307727c980f33faed
- Size of remote file:
- 3.04 kB
- SHA256:
- 64701d819b7c5bd75f785261515ce586b6053ac1f4b5469810c816ff4fac7829
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.