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Bertbek News Big Cased

Developed by elmurod1202
A pre-trained BERT model for Uzbek (12-layer, case-sensitive), trained on a large news corpus (Daryo)
Downloads 141
Release Time : 6/14/2023

Model Overview

This model is a pre-trained BERT model for Uzbek, primarily used for natural language processing tasks such as text classification and named entity recognition.

Model Features

Uzbek Language Support
Specifically pre-trained for Uzbek, suitable for natural language processing tasks in Uzbek.
Based on News Corpus
The model is trained on a large news corpus (Daryo), making it suitable for news-related text processing tasks.
Case-Sensitive
The model is case-sensitive, better handling case-sensitive tasks in Uzbek.

Model Capabilities

Text classification
Named entity recognition
Text generation
Language understanding

Use Cases

News Processing
News Classification
Classify Uzbek news into categories such as politics, economy, sports, etc.
Named Entity Recognition
Identify entities such as person names, locations, and organization names from news texts.
Language Understanding
Semantic Analysis
Analyze the semantics of Uzbek texts for tasks like sentiment analysis and intent recognition.
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