| --- |
| license: apache-2.0 |
| language: |
| - tr |
| library_name: transformers |
| pipeline_tag: feature-extraction |
| --- |
| |
| # TyBert Model |
|
|
| This repository provides a pretrained Bert model for Turkish by Trendyol, named TyBert. The model is useful for various natural language understanding tasks, such as text classification, named entity recognition, and more. |
|
|
|
|
| ## How to use |
|
|
| ```python |
| from transformers import BertTokenizer, BertModel |
| |
| # Load the tokenizer and model |
| tokenizer = BertTokenizer.from_pretrained("Trendyol/tybert") |
| model = BertModel.from_pretrained("Trendyol/tybert") |
| |
| # Define a sample text |
| text = "Filenin Sultanları ilk maçını 29 Temmuz'da Hollanda'ya karşı oynayacak." |
| |
| # Tokenize and encode the input text |
| encoded_input = tokenizer(text, return_tensors='pt') |
| |
| # Get the model's output |
| output = model(**encoded_input) |
| |
| print(output) |
| |
| ``` |
