Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use mtlulka/a2c-PandaReachDense-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use mtlulka/a2c-PandaReachDense-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="mtlulka/a2c-PandaReachDense-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from mtlulka/a2c-PandaReachDense-v2: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/mtlulka/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://mtlulka/a2c-PandaReachDense-v2/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/mtlulka/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
3.06 kB
- Xet hash:
- 5053312d7716ffdf6150ad9ceff2a456e0ab280f3dbc89cdfd686aca631b6581
- Size of remote file:
- 3.06 kB
- SHA256:
- 6e6fbb23a35ee64701a4027533de0cabdd0701b5ba8d94651066344f148aacc7
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