Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
SegformerForSemanticSegmentation
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background
background-removal
Pytorch
vision
legal liability
custom_code
Instructions to use algonia/rembg_clone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use algonia/rembg_clone with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="algonia/rembg_clone", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("algonia/rembg_clone", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 805f50e7943f8be300f41f002e14420fbac3d2e5398b0aa796ca6537bcb7df68
- Size of remote file:
- 2.16 MB
- SHA256:
- 43a9453f567d9bff7fe4481205575bbf302499379047ee6073247315452ba8fb
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