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mult-skill-act-models
QRP123/mult-skill-act-models
mult-skill-act-models is a machine learning model from QRP123. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Multi-skill Action Chunking Transformer models for Piper dual-arm robot.
Access
Public
Updated Mar 2, 2026
Repo size
2.6 GB
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At a glance
- Access
- Public
- Created
- Mar 2, 2026
- Updated
- Mar 2, 2026
- SHA
- f754dbd7
Model card
From the Hugging Face model README
Mult-skill ACT Models
Multi-skill Action Chunking Transformer models for Piper dual-arm robot.
Models
| Model | Description |
|---|---|
point_classifier/ | ResNet-18 point classifier (10 classes: point1-point10) |
exp1_all_points/ | ACT policy trained on all 150 episodes (10 points combined) |
exp2_point1/ ~ exp2_point10/ | ACT policies trained per-point (15 episodes each) |
exp3_act_x/ | Experimental ACT policy |
Normalization
normalization/ contains pre-computed normalization constants for each dataset:
all_points_v30_norm.py- Stats from combined datasetpoint1_v30_norm.py~point10_v30_norm.py- Stats from per-point datasets
Usage
Download all models
pip install huggingface_hub
huggingface-cli download QRP123/mult-skill-act-models --repo-type model --local-dir ./models
Point Classifier Inference
from point_classifier_model import PointClassifier
import torch
checkpoint = torch.load("point_classifier/point_classifier_best.pth")
model = PointClassifier(num_classes=10, pretrained=False)
model.load_state_dict(checkpoint["model_state_dict"])
Robot Setup
- Robot: Piper dual-arm (7D + 7D = 14D state/action)
- Cameras: fisheye_left, fisheye_right, wide_mid, wide_top (256x256)
- FPS: 30
- Created
- Mar 2, 2026
- Updated
- Mar 2, 2026