Instructions to use prithivMLmods/Fashion-Mnist-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Fashion-Mnist-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Fashion-Mnist-SigLIP2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Fashion-Mnist-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Fashion-Mnist-SigLIP2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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fn=fashion_mnist_classification,
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inputs=gr.Image(type="numpy"),
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outputs=gr.Label(label="Prediction Scores"),
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title="Fashion MNIST Classification",
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description="Upload an image to classify it into one of the 10 Fashion-MNIST categories."
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)
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fn=fashion_mnist_classification,
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inputs=gr.Image(type="numpy"),
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outputs=gr.Label(label="Prediction Scores"),
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title="Fashion MNIST Classification Labels",
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description="Upload an image to classify it into one of the 10 Fashion-MNIST categories."
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)
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