Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use aymenkhs/a2c-PandaReachDense-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use aymenkhs/a2c-PandaReachDense-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="aymenkhs/a2c-PandaReachDense-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from aymenkhs/a2c-PandaReachDense-v2: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/aymenkhs/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://aymenkhs/a2c-PandaReachDense-v2/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/aymenkhs/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
3.06 kB
- Xet hash:
- a97b6b9e7930d91291ff263b9c6f3440203455dfe7e6206b6798d1170571ea90
- Size of remote file:
- 3.06 kB
- SHA256:
- a490fed9de41df3ed9dc3df4d6e61eb0fc8296f7fb59bbdc4b619462bfd266b6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.