Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use gugaaa/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use gugaaa/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="gugaaa/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from gugaaa/a2c-PandaReachDense-v3: direct link, hf CLI and curl.
- Browser
- Download file 2.65 kB
-
https://huggingface.co/gugaaa/a2c-PandaReachDense-v3/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://gugaaa/a2c-PandaReachDense-v3/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/gugaaa/a2c-PandaReachDense-v3/resolve/main/vec_normalize.pkl
2.65 kB
- Xet hash:
- c0f35bf1ee3bd51970956acc6dbe681bb7a745f0769cd268907d594afe6a00ba
- Size of remote file:
- 2.65 kB
- SHA256:
- 3e685a2ad8bc36b5a1ea5721540da0e28f251582e49c34f9d140b131de8af2b8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.