Reinforcement Learning
stable-baselines3
BipedalWalker-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use bvk1ng/bipedal_walker_ppo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use bvk1ng/bipedal_walker_ppo with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="bvk1ng/bipedal_walker_ppo", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Proximal Policy Optimisation (PPO) Agent playing BipedalWalker-v3
This is a trained model of a Proximal Policy Optimisation (PPO) agent playing BipedalWalker-v3 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
- 2
Evaluation results
- mean_reward on BipedalWalker-v3self-reported209.63 +/- 82.30