Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
Transformers.js
SegformerForSemanticSegmentation
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Pytorch
vision
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custom_code
Instructions to use briaai/RMBG-1.4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use briaai/RMBG-1.4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="briaai/RMBG-1.4", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("briaai/RMBG-1.4", trust_remote_code=True, device_map="auto") - Transformers.js
How to use briaai/RMBG-1.4 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-segmentation', 'briaai/RMBG-1.4'); - Notebooks
- Google Colab
- Kaggle
Download example_input.jpg from briaai/RMBG-1.4: direct link, hf CLI and curl.
- Browser
- Download file 327 kB
-
https://huggingface.co/briaai/RMBG-1.4/resolve/main/example_input.jpg
- Command line
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hf download hf://briaai/RMBG-1.4/example_input.jpg
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curl -L -o example_input.jpg https://huggingface.co/briaai/RMBG-1.4/resolve/main/example_input.jpg
327 kB
