Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use nokotin/a2c-PandaReachDense-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use nokotin/a2c-PandaReachDense-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="nokotin/a2c-PandaReachDense-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from nokotin/a2c-PandaReachDense-v2: direct link, hf CLI and curl.
- Browser
- Download file 2.39 kB
-
https://huggingface.co/nokotin/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://nokotin/a2c-PandaReachDense-v2/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/nokotin/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
2.39 kB
- Xet hash:
- 6d167a57f88e8c41850bf91a52345b9fcc65d9e84a594a6ed9c2feb4f1364ddc
- Size of remote file:
- 2.39 kB
- SHA256:
- 3b400664656e94f770d71ff21e29e44ae9b4807694de06c299ee325d45297d29
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.