Reinforcement Learning
stable-baselines3
HumanoidStandup-v5
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use farama-minari/HumanoidStandup-v5-SAC-simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use farama-minari/HumanoidStandup-v5-SAC-simple with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="farama-minari/HumanoidStandup-v5-SAC-simple", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
SAC Agent playing HumanoidStandup-v5
This is a trained model of a SAC agent playing HumanoidStandup-v5 using the stable-baselines3 library.
Usage (with Stable-baselines3)
TODO: Add your code
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
- Downloads last month
- -
Evaluation results
- mean_reward on HumanoidStandup-v5self-reported164885.84 +/- 22752.13