# News text processing

A fine-tuned Russian small sentence similarity model based on cointegrated/rubert-tiny2, suitable for feature extraction and sentence transformation tasks

Persian text summarization model based on MT5 architecture, fine-tuned on TasnimNews dataset

A summarization model fine-tuned from google/mt5-small on the CNN/DailyMail dataset, suitable for English text summarization tasks.

UzRoBerta is a pre-trained Uzbek (Cyrillic script) model for masked language modeling and next sentence prediction.

A financial news sentiment analysis model fine-tuned based on DistilRoBERTa, with an accuracy rate of 98.23%.

This is a text summarization model based on the mT5-small architecture, fine-tuned on the German MLSUM dataset

This is a text summarization model fine-tuned on the Spanish BERT model (BETO), specifically designed for automatic summarization of Spanish texts.

A Korean pre-trained language model based on the BERT architecture, suitable for Korean text processing tasks.

A fine-tuned abstract generation model based on PegasusXSUM for German datasets

Amharic language model fine-tuned based on multilingual BERT, achieved by vocabulary replacement and fine-tuning, outperforming the original multilingual model in NER tasks

A DistilBERT fine-tuned model for English text punctuation restoration, specifically designed to add punctuation to lowercase English text without punctuation.

A Chinese punctuation restoration model fine-tuned based on DistilBertForTokenClassification, specifically designed to add punctuation marks to unpunctuated Chinese text