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Fine-tuning large language models (LLMs) for Amharic Named Entity Recognition (NER) to support a centralized telegram e-commerce platform

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Heban-7/Amharic-NER

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Amharic-NER

Fine-tuning large language models (LLMs) for Amharic Named Entity Recognition (NER) to support a centralized telegram e-commerce platform

Project Objective

This project focuses on fine-tuning LLM’s for Amharic Named Entity Recognition (NER) system that extracts key business entities such as product names, prices, and Locations, from text, images, and documents shared across these Telegram channels. The extracted data will be used to populate EthioMart's centralised database, making it a comprehensive e-commerce hub.

Data Extraction

Data Extracted from Telegram Channels

  • @ethio_brand_collection
  • @gebeyaadama
  • @ZemenExpress
  • @nevacomputer
  • @MerttEka
  • @Shewabrand
  • @Fashiontera
  • @marakibrand
  • @belaclassic

Key Objectives:

  • Realtime data extraction from telegram channel
  • Fine tuning LLM to extract Entities like Product name, price location

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Fine-tuning large language models (LLMs) for Amharic Named Entity Recognition (NER) to support a centralized telegram e-commerce platform

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