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- biology
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- SigLIP2
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# **Trash-Net**
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> **Trash-Net** is an image classification vision-language encoder model fine-tuned from **google/siglip2-base-patch16-224** for a single-label classification task. It is designed to classify images of waste materials into different categories using the **SiglipForImageClassification** architecture.
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- **Waste Management:** Assisting in automated waste sorting and recycling.
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- **Environmental Monitoring:** Identifying and categorizing waste in public spaces.
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- **Educational Purposes:** Teaching waste classification and sustainability.
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- **Smart Cities:** Enhancing waste disposal systems through AI-driven classification.
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- biology
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- SigLIP2
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---
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# **Trash-Net**
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> **Trash-Net** is an image classification vision-language encoder model fine-tuned from **google/siglip2-base-patch16-224** for a single-label classification task. It is designed to classify images of waste materials into different categories using the **SiglipForImageClassification** architecture.
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- **Waste Management:** Assisting in automated waste sorting and recycling.
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- **Environmental Monitoring:** Identifying and categorizing waste in public spaces.
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- **Educational Purposes:** Teaching waste classification and sustainability.
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- **Smart Cities:** Enhancing waste disposal systems through AI-driven classification.
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