# RoBERTa Architecture

A medical domain named entity recognition model based on the RoBERTa architecture, used to identify specific entities from medical texts

Chinese pre-trained model based on RoBERTa architecture, supporting text-to-speech tasks

An AI-generated text detector based on multi-scale positive unlabeled detection method, used to identify AI-generated text content.

DrBERT is a French RoBERTa model trained on the open-source French medical text corpus NACHOS, specializing in the biomedical and clinical fields

Danish BERT is a language model optimized for Danish, excelling in the Danish ScandEval benchmark.

A multilingual named entity recognition model fine-tuned on the PANX dataset based on the xlm-roberta-base model

A question-answering model fine-tuned on the SQuAD 2.0 dataset based on RoBERTa-base, designed to answer questions based on given text

A Korean semantic similarity calculation model optimized based on the RoBERTa architecture, achieving high-performance sentence embeddings through multi-task learning

A BERT large model pretrained on English legal and administrative texts using RoBERTa pretraining objectives

An Icelandic masked language model based on the RoBERTa-base architecture, fine-tuned from xlm-roberta-base

Icelandic masked language model trained on RoBERTa-base architecture using the fairseq framework

This model is a French text summarization model based on the CamemBERT architecture, specifically fine-tuned for French news summarization tasks.

This model is based on the RoBERTa architecture and trained using the CrossEncoder class from SentenceTransformers, specifically designed for detecting duplicate questions on Quora.

Catalan text entailment model based on RoBERTa architecture, fine-tuned on the TE-ca dataset

A QA model fine-tuned on the SQuAD dataset using few-shot learning based on RoBERTa-base

RobBERT is the state-of-the-art Dutch BERT model, pretrained on a large scale and adaptable to various text tasks through fine-tuning.

A Q&A model fine-tuned on the SQuAD 2.0 dataset based on the RoBERTa-base model

A Japanese RoBERTa-based pretrained model, trained on Japanese Wikipedia and the Japanese portion of CC-100.

This is a Spanish fill-mask model based on the RoBERTa-base architecture, trained from scratch.

This is a sentence similarity calculation model based on the RoBERTa architecture, supporting Chinese text processing

Data2Vec NLP Base is a natural language processing model converted from the fairseq framework, suitable for tasks such as text classification.

An encoder-decoder model based on the RoBERTa architecture, specifically designed for sentence fusion tasks

A cloned version of the RoBERTa-based text toxicity classifier for evaluating text detoxification algorithm effectiveness

This is a sentence embedding model based on sentence-transformers, which can map text to a 768-dimensional vector space and is suitable for sentence similarity calculation and semantic search tasks.

A cross-encoder based on RoBERTa-base for predicting semantic similarity scores (0-1) between two sentences.

This model is based on the RoBERTa architecture and fine-tuned on the SQuAD1.1 dataset, capable of extracting answers to questions from given contexts.

Pretrained Uzbek (Cyrillic & Latin alphabets) masked language modeling and sentence prediction model

This is a sentence transformer model based on allenai/biomed_roberta_base, specifically fine-tuned for sentence similarity tasks, capable of mapping text to a 768-dimensional vector space.

SanBERTa is a RoBERTa model trained on Sanskrit text, specifically designed for Sanskrit text processing tasks.

A Sundanese masked language model based on the RoBERTa architecture, trained on multiple datasets.

This is a model based on the RoBERTa-base architecture, fully trained from scratch using Spanish data, specializing in masked language modeling tasks.

A base-sized Japanese RoBERTa model trained by rinna Co., Ltd., suitable for masked language modeling tasks in Japanese text.

A QA model fine-tuned on the SQuAD dataset based on RoBERTa-base, suitable for reading comprehension tasks

This is a RoBERTa-like language model trained on partial data from the TAIGA corpus, primarily for Russian text processing.

Indonesian masked language model based on RoBERTa architecture, trained on the OSCAR corpus with a validation accuracy of 62.45%

KLUE-RoBERTa-large is a Korean pre-trained language model based on the RoBERTa architecture, developed by a Korean research team and optimized for Korean natural language processing tasks.

Advanced French language model based on the RoBERTa architecture, compatible with the TensorFlow framework

A RoBERTa BASE model pretrained on Thai Wikipedia, suitable for Thai text processing tasks

A RoBERTa model pre-trained on classical Chinese, suitable for ancient text processing tasks

TajBERTo is the first RoBERTa-like language model for the Tajik language, specifically designed for Tajik natural language processing tasks.