Image Segmentation
Transformers
English
clipseg
segmentation
construction
drywall
quality-assurance
text-conditioned
binary-mask
Instructions to use youngPhilosopher/drywall-qa-clipseg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use youngPhilosopher/drywall-qa-clipseg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="youngPhilosopher/drywall-qa-clipseg")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("youngPhilosopher/drywall-qa-clipseg", dtype="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- fb5f592fb26de0c6fa365feae0022a292a05bcb8ae1dbfc204ce5f0f0acc3c5d
- Size of remote file:
- 1.9 MB
- SHA256:
- 721c8bef97164440065e3b1417f0ac62c2ed1cc116878bf377ad97ed6376c4a8
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