metadata
license: mit
library_name: pytorch
tags:
- reinforcement-learning
- locomotion
- robotics
- g1
g1-walk
PyTorch checkpoint for a G1 humanoid locomotion policy trained with ADD (Adversarial Differential Discriminators).
Checkpoint info
| Key | Value |
|---|---|
| Training iterations | 9,900 |
| Total environment samples | 5,190,975,488 |
| Number of parameters | 3,712,535 |
Usage
import torch
checkpoint = torch.load("model.pt", map_location="cpu")
state_dict = checkpoint["model"]
# Load into your agent:
# agent.load_state_dict(state_dict)