Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
Transformers.js
English
segformer
vision
nvidia/mit-b5
Instructions to use jayson1408/faceparsing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayson1408/faceparsing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="jayson1408/faceparsing")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("jayson1408/faceparsing") model = SegformerForSemanticSegmentation.from_pretrained("jayson1408/faceparsing") - Transformers.js
How to use jayson1408/faceparsing with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-segmentation', 'jayson1408/faceparsing'); - Notebooks
- Google Colab
- Kaggle
File size: 749 Bytes
cce9ed4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | {
"per_channel": true,
"reduce_range": true,
"per_model_config": {
"model": {
"op_types": [
"Unsqueeze",
"Shape",
"Transpose",
"Sqrt",
"Gather",
"Slice",
"Erf",
"Div",
"Reshape",
"Add",
"Cast",
"Sub",
"Concat",
"ReduceMean",
"Mul",
"Conv",
"Constant",
"Resize",
"Softmax",
"Pow",
"Relu",
"MatMul"
],
"weight_type": "QUInt8"
}
}
} |