Instructions to use maheeswar/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use maheeswar/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="maheeswar/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
a2c-PandaReachDense-v3
This is a trained model of a Reinforcement Learning agent for PandaReachDense-v3 using stable-baselines3. Created for the Hugging Face Deep RL Course.
Evaluation Results
- Mean Reward: -0.50 +/- 0.10
- Target Environment:
PandaReachDense-v3 - Library:
stable-baselines3 - Model Architecture:
A2C
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Evaluation results
- reward on PandaReachDense-v3self-reported-0.50 +/- 0.10