Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use mobiusmatt/a2c-PandaReachDense-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use mobiusmatt/a2c-PandaReachDense-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="mobiusmatt/a2c-PandaReachDense-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from mobiusmatt/a2c-PandaReachDense-v2: direct link, hf CLI and curl.
- Browser
- Download file 2.38 kB
-
https://huggingface.co/mobiusmatt/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://mobiusmatt/a2c-PandaReachDense-v2/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/mobiusmatt/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
2.38 kB
- Xet hash:
- c77197e40f80c08bcca280bb982e981c89e2bf25d113cc7abe43e4b5d4491929
- Size of remote file:
- 2.38 kB
- SHA256:
- ae702066e892ac4712016b897544f5b1a7fc8eb8023aa039e8add500bf2a0fcb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.