Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use macdog101/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use macdog101/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="macdog101/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from macdog101/a2c-PandaReachDense-v3: direct link, hf CLI and curl.
- Browser
- Download file 2.66 kB
-
https://huggingface.co/macdog101/a2c-PandaReachDense-v3/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://macdog101/a2c-PandaReachDense-v3/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/macdog101/a2c-PandaReachDense-v3/resolve/main/vec_normalize.pkl
2.66 kB
- Xet hash:
- 679d8d20a3ad8f88bb78e4a0e9468ab40e3be98ee3fe52e36dab6f3e8f6964b7
- Size of remote file:
- 2.66 kB
- SHA256:
- 1f2a7d4608fdccdb395e6d1b3fa2b76693f6f727651b53856c3dfe0763bce460
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.