# Sequence labeling

French token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

BERT-base-cased fine-tuned Named Entity Recognition (NER) model

A named entity recognition model fine-tuned on the CoNLL2003 dataset based on the RoBERTa-large model, demonstrating excellent performance in NER tasks.

A lightweight named entity recognition model based on DistilBERT, fine-tuned on the conll2003 dataset

A lightweight named entity recognition model based on DistilBERT, fine-tuned on the conll2003 dataset, featuring efficient inference performance and high accuracy.

This model is a named entity recognition (NER) model trained on the HiNER-original dataset based on the XLM-RoBERTa-large architecture, specifically designed for token classification tasks.

Named Entity Recognition (NER) model fine-tuned based on xlm-roberta-base, demonstrating excellent performance on the evaluation set (F1 score 0.9777)

Flair's built-in English fast phrase chunking model for identifying grammatical structures such as noun phrases and verb phrases in sentences.

A lightweight named entity recognition model based on DistilBERT, fine-tuned on the CoNLL2003 dataset, suitable for entity labeling tasks in English text.

Named Entity Recognition (NER) model fine-tuned on the conll2003 dataset based on DeBERTa-base

Swedish NER model based on KB-BERT architecture, fine-tuned on SUCX 3.0 NER corpus while preserving original case features

This model is a Named Entity Recognition (NER) model fine-tuned on the conll2003 dataset based on the ALBERT-base-v2 architecture, demonstrating excellent performance in entity recognition tasks.