Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use z4x/a2c-PandaReachDense-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use z4x/a2c-PandaReachDense-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="z4x/a2c-PandaReachDense-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from z4x/a2c-PandaReachDense-v2: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/z4x/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://z4x/a2c-PandaReachDense-v2/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/z4x/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
3.06 kB
- Xet hash:
- ce298ea0a41b06c6aaeb7fc90f23f88459478953917e89b83880c387eadff542
- Size of remote file:
- 3.06 kB
- SHA256:
- dd2e01e8cc191f0fb209daf30aae6d4d99aca70008ba46b1f0198f475861723b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.