Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use llmvetter/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use llmvetter/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="llmvetter/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90e0fa19ca0d056c9c42a30f5a7797601a70bcdaa40bb80b03cdde8b285fa830
- Size of remote file:
- 2.65 kB
- SHA256:
- 223d0f03359c5ad2ecaa5c3b8c74f29d7a036d88a1df082916dedb4e69f51861
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