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
Upload .gitignore with huggingface_hub
Browse files- .gitignore +36 -0
.gitignore
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# Python-generated files
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__pycache__/
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*.py[oc]
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build/
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dist/
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wheels/
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*.egg-info
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# Virtual environments
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.venv
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# Assessment prompt — do not publish
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Problem.md
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# macOS
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.DS_Store
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# Data (too large for git)
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data/raw/
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data/processed/
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data/splits/
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# Model checkpoints (too large for git)
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outputs/checkpoints/
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# Prediction masks (too many files)
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outputs/masks/
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# Editor
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.idea/
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.vscode/
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*.swp
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# Claude
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.claude/
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last-output.md
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