Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Kittitouch/a2c-PandaReachDense-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Kittitouch/a2c-PandaReachDense-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Kittitouch/a2c-PandaReachDense-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from Kittitouch/a2c-PandaReachDense-v2: direct link, hf CLI and curl.
- Browser
- Download file 3.21 kB
-
https://huggingface.co/Kittitouch/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://Kittitouch/a2c-PandaReachDense-v2/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/Kittitouch/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
3.21 kB
- Xet hash:
- 55f7896183a93958f3732f2613ab635971fdc87763db45cda4caa6e3c0d48382
- Size of remote file:
- 3.21 kB
- SHA256:
- dcac6cc895eb2e5c2f3dbbbb7b8fc6d0a0bf710626a8aa7a19277a42c8330e37
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