Instructions to use softdev629/qb0hif0y with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use softdev629/qb0hif0y with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="softdev629/qb0hif0y") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("softdev629/qb0hif0y") model = AutoModelForImageClassification.from_pretrained("softdev629/qb0hif0y") - Notebooks
- Google Colab
- Kaggle
Update model_card.json
Browse files- model_card.json +3 -3
model_card.json
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{
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"model_name": "roadwork-snapshot-
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"description": "Snapshot model from natix-network-org/
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"version": "1.0.
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"submitted_by": "5HKVvLofmoGwGGbhcuPC577bQt3Dg383WxTS8p12ZP5GHvd4",
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"submission_time": 1748994355
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}
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{
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"model_name": "roadwork-snapshot-qb0hif0y1",
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"description": "Snapshot model from natix-network-org/roadwork1",
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"version": "1.0.1",
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"submitted_by": "5HKVvLofmoGwGGbhcuPC577bQt3Dg383WxTS8p12ZP5GHvd4",
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"submission_time": 1748994355
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}
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