Image Classification
Transformers
Safetensors
English
metaclip_2
text-generation-inference
gender-identifier
Instructions to use prithivMLmods/MetaCLIP-2-Gender-Identifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/MetaCLIP-2-Gender-Identifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/MetaCLIP-2-Gender-Identifier") 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/MetaCLIP-2-Gender-Identifier") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/MetaCLIP-2-Gender-Identifier") - Notebooks
- Google Colab
- Kaggle
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README.md
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- gender-identifier
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---
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fn=age_classification,
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inputs=gr.Image(type="numpy", label="Upload Image"),
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outputs=gr.Label(label="Predicted Gender"),
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title="MetaCLIP-2-
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description="Upload an image to predict the person's gender."
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)
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- gender-identifier
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---
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# **MetaCLIP-2-Gender-Identifier**
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from PIL import Image
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# Model name from Hugging Face Hub
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model_name = "prithivMLmods/MetaCLIP-2-Gender-Identifier"
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# Load processor and model
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processor = AutoImageProcessor.from_pretrained(model_name)
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fn=age_classification,
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inputs=gr.Image(type="numpy", label="Upload Image"),
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outputs=gr.Label(label="Predicted Gender"),
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title="MetaCLIP-2-Gender-Identifier",
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description="Upload an image to predict the person's gender."
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)
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