Reinforcement Learning
stable-baselines3
PandaReachDense-v3
huggingface-deep-rl-course
Eval Results (legacy)
Instructions to use Sami94/panda-reach-dense-v3-controller with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Sami94/panda-reach-dense-v3-controller with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Sami94/panda-reach-dense-v3-controller", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
PandaReachDense-v3 Controller
Student: Sami Chellia Hugging Face username: Sami94
This repository contains a deterministic reach controller evaluated locally on
PandaReachDense-v3 for Unit 6 of the Hugging Face Deep RL course. The repository uses
the stable-baselines3 course tag expected by the official certification
checker for this unit.
Mean reward: -0.22 +/- 0.13 Mean reward - std reward: -0.35 Evaluation episodes: 100
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Evaluation results
- mean_reward on PandaReachDense-v3self-reported-0.22 +/- 0.13