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Bert2d Cased Turkish 128K WWM NSW2

Developed by yigitbekir
Bert2DModel is a brand-new exploration of the classic BERT architecture, designed specifically for languages with complex lexical structures like Turkish.
Downloads 610
Release Time : 5/22/2025

Model Overview

Through a unique 'two-dimensional embedding' system, Bert2DModel not only focuses on the position of words in a sentence but also considers the positions of sub-parts within words, enabling a deeper understanding of grammar and semantics. The first version of this model was trained for Turkish.

Model Features

Two-dimensional embedding system
By simultaneously considering the position of words in a sentence and the positions of sub-parts within words, it enables a deeper understanding of grammar and semantics.
Optimized for Turkish
Specifically designed for languages with complex lexical structures like Turkish.
Custom configuration parameters
Introduces new configuration parameters that do not exist in the standard BERT model, such as max_word_position_embeddings and max_intermediate_subword_position_embeddings.

Model Capabilities

Turkish text understanding
Fill-mask task
Text classification
Tag classification

Use Cases

Text understanding
Occupation prediction
Predict the missing occupation information in a sentence.
For example: 'Adamın mesleği [MASK] midir acaba?' may be predicted as'mühendis' (engineer) or 'doktor' (doctor).
Grammar analysis
Parsing of complex lexical structures
Parse the complex lexical structures in Turkish.
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