Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Yashu-0099/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Yashu-0099/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Yashu-0099/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
A2C Agent playing PandaReachDense-v3
This is a trained model of an A2C agent playing PandaReachDense-v3 using the stable-baselines3 library.
Evaluation Result
- Mean Reward: -0.21 +/- 0.08
- Threshold: -3.5 (Solved)
- Downloads last month
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Evaluation results
- mean_reward on PandaReachDense-v3self-reported-0.21 +/- 0.08