Reinforcement Learning
stable-baselines3
BipedalWalkerHardcore-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use SimingSiming/ppo-BipedalWalkerHardcore-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use SimingSiming/ppo-BipedalWalkerHardcore-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="SimingSiming/ppo-BipedalWalkerHardcore-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
| library_name: stable-baselines3 | |
| tags: | |
| - BipedalWalkerHardcore-v3 | |
| - deep-reinforcement-learning | |
| - reinforcement-learning | |
| - stable-baselines3 | |
| model-index: | |
| - name: PPO | |
| results: | |
| - metrics: | |
| - type: mean_reward | |
| value: 7.09 +/- 2.73 | |
| name: mean_reward | |
| task: | |
| type: reinforcement-learning | |
| name: reinforcement-learning | |
| dataset: | |
| name: BipedalWalkerHardcore-v3 | |
| type: BipedalWalkerHardcore-v3 | |
| # parameters <br> | |
| model = A2C(policy = "MlpPolicy", <br> | |
| env = env, <br> | |
| n_steps = 256, <br> | |
| learning_rate = 0.001, <br> | |
| gamma = 0.99, <br> | |
| verbose=1) <br> |