Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use monti-python/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use monti-python/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="monti-python/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 333ada6d9e7363b75a2aed5ec3ce2b8fe456ace902032d083a95df6e24f7b18d
- Size of remote file:
- 2.65 kB
- SHA256:
- 21b931c2c2ccb916b35a6fb460c655e93118172ba878e51f58ca2bbbe40583a4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.