Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use rondahahda/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use rondahahda/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="rondahahda/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
A2C Agent playing PandaReachDense-v3
A trained A2C agent playing PandaReachDense-v3, made with the stable-baselines3 library.
Usage
from huggingface_sb3 import load_from_hub
from stable_baselines3 import A2C
checkpoint = load_from_hub("rondahahda/a2c-PandaReachDense-v3", "a2c-PandaReachDense-v3.zip")
model = A2C.load(checkpoint)
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Evaluation results
- mean_reward on PandaReachDense-v3self-reported-0.16 +/- 0.06