Reinforcement Learning
stable-baselines3
PandaReachJointsDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use mtalec/a2c-panda-reach with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use mtalec/a2c-panda-reach with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="mtalec/a2c-panda-reach", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from mtalec/a2c-panda-reach: direct link, hf CLI and curl.
- Browser
- Download file 2.54 kB
-
https://huggingface.co/mtalec/a2c-panda-reach/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://mtalec/a2c-panda-reach/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/mtalec/a2c-panda-reach/resolve/main/vec_normalize.pkl
2.54 kB
- Xet hash:
- 8c62a69ec1ca191cfa71743d8947e00a163d8207edea7e7a7cd8afe6e5194d4e
- Size of remote file:
- 2.54 kB
- SHA256:
- 0f37c9ed4a50f6ca6e222b2e41e7aac89cbb947335ca1eff7a63f9f0bab8f739
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