Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
Transformers.js
SegformerForSemanticSegmentation
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background
background-removal
Pytorch
vision
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custom_code
Instructions to use SolonD/RMBG-1.4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SolonD/RMBG-1.4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="SolonD/RMBG-1.4", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("SolonD/RMBG-1.4", trust_remote_code=True, dtype="auto") - Transformers.js
How to use SolonD/RMBG-1.4 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-segmentation', 'SolonD/RMBG-1.4'); - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- abfd88fffd7fb95a9d72a8d7361218fca6c9e014c6d427e9c65757ca9103f9ab
- Size of remote file:
- 177 MB
- SHA256:
- 893c16c340b1ddafc93e78457a4d94190da9b7179149f8574284c83caebf5e8c
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