cihatyldz/carsi-bert-turkish-ecommerce-ner
Token Classification • 0.1B • Updated • 35
Cihat Yıldız PRO
cihatyldz
AI & ML interests
Senior Data Scientist | MSc
Recent Activity
liked a model about 16 hours ago
dbmdz/bert-base-turkish-cased liked a model about 16 hours ago
sentence-transformers/all-MiniLM-L12-v2 posted an update 4 days ago
Çarşı, a dual-model Turkish e-commerce NER demo, is now live on Spaces. It performs side-by-side Named Entity Recognition using a fine-tuned Turkish BERT and Qwen2.5-7B zero-shot extraction for real-time evaluation of the "Specialized NER vs. Zero-shot LLM" trade-offs. The system extracts 7 entity types from Turkish e-commerce text — PRODUCT, BRAND, PRICE, COLOR, SIZE, MATERIAL, and GENDER — with color-coded entity highlighting. The fine-tuned BERT delivers ~10-50ms inference on CPU while the LLM handles flexible extraction via HF Inference API, trained on 8,000 synthetic Turkish e-commerce sentences with BIO-tagged token classification.
🧠 BERT model: https://huggingface.co/cihatyldz/carsi-bert-turkish-ecommerce-ner
📊 Dataset: https://huggingface.co/datasets/cihatyldz/carsi-turkish-ecommerce-ner
🤗 Demo: https://huggingface.co/spaces/cihatyldz/carsi-ecommerce-nerOrganizations
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