Instructions to use prithivMLmods/Multilabel-Portrait-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Multilabel-Portrait-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Multilabel-Portrait-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/Multilabel-Portrait-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Multilabel-Portrait-SigLIP2") - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
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license: apache-2.0
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---
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```py
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Classification Report:
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precision recall f1-score support
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Anime Portrait 0.9989 0.9991 0.9990 4444
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Cartoon Portrait 0.9964 0.9926 0.9945 4444
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Real Portrait 0.9964 0.9971 0.9967 4444
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Sketch Portrait 0.9971 1.0000 0.9985 4444
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accuracy 0.9972 17776
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macro avg 0.9972 0.9972 0.9972 17776
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weighted avg 0.9972 0.9972 0.9972 17776
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```
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