Image Classification
Transformers
Safetensors
English
siglip
Age
Detection
Siglip2
ViT
AutoImageProcessor
0-60+
Instructions to use prithivMLmods/Age-Classification-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Age-Classification-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Age-Classification-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/Age-Classification-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Age-Classification-SigLIP2") - Inference
- Notebooks
- Google Colab
- Kaggle
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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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Child 0-12 0.9744 0.9562 0.9652 2193
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Teenager 13-20 0.8675 0.7032 0.7768 1779
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Adult 21-44 0.9053 0.9769 0.9397 9999
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Middle Age 45-64 0.9059 0.8317 0.8672 3785
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Aged 65+ 0.9144 0.8397 0.8755 1260
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accuracy 0.9109 19016
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macro avg 0.9135 0.8615 0.8849 19016
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weighted avg 0.9105 0.9109 0.9087 19016
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```
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