Reinforcement Learning
stable-baselines3
PandaPickAndPlace-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use jlse/a2c-PandaPickAndPlace-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use jlse/a2c-PandaPickAndPlace-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="jlse/a2c-PandaPickAndPlace-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from jlse/a2c-PandaPickAndPlace-v3: direct link, hf CLI and curl.
- Browser
- Download file 3.04 kB
-
https://huggingface.co/jlse/a2c-PandaPickAndPlace-v3/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://jlse/a2c-PandaPickAndPlace-v3/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/jlse/a2c-PandaPickAndPlace-v3/resolve/main/vec_normalize.pkl
3.04 kB
- Xet hash:
- 0310eb8dc102628b5d37253cee9ae036875a6650b57da632c76f1b9b2092e4db
- Size of remote file:
- 3.04 kB
- SHA256:
- 8d99ff9e3eb87487fa8e8be21c5b768f13db29bf089b3b8809c009e891e30dbb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.