Image Segmentation
Transformers
ONNX
Transformers.js
English
u2net
mask-generation
vision
background-removal
portrait-matting
Instructions to use LEO-LLLL/U-2-Net with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LEO-LLLL/U-2-Net with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="LEO-LLLL/U-2-Net")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LEO-LLLL/U-2-Net", dtype="auto") - Transformers.js
How to use LEO-LLLL/U-2-Net with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-segmentation', 'LEO-LLLL/U-2-Net'); - Notebooks
- Google Colab
- Kaggle
File size: 389 Bytes
ff27042 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"_name_or_path": "u2net",
"model_type": "u2net",
"architectures": [
"U2NetModel"
],
"transformers.js_config": {
"dtype": "fp32"
},
"input_name": ["input.1"],
"input_shape": [1, 3, 320, 320],
"output_composite": "1959",
"output_names": [
"1959",
"1960",
"1961",
"1962",
"1963",
"1964",
"1965"
],
"output_shape": [1, 320, 320]
}
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