Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use jvilaseca/a2c-PandaReachDense-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use jvilaseca/a2c-PandaReachDense-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="jvilaseca/a2c-PandaReachDense-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from jvilaseca/a2c-PandaReachDense-v2: direct link, hf CLI and curl.
- Browser
- Download file 2.39 kB
-
https://huggingface.co/jvilaseca/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://jvilaseca/a2c-PandaReachDense-v2/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/jvilaseca/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
2.39 kB
- Xet hash:
- 38960caef4cf0fdb76119111368376672b0b056433969160bfa3a61e96f53f8a
- Size of remote file:
- 2.39 kB
- SHA256:
- c0ab72d2993582763c84de5efafb6f4354a245c4178284392c3d69b66ae60828
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