# Multi-entity Recognition

EntityBERT is a lightweight, fine-tuned Transformer model designed specifically for the Named Entity Recognition (NER) task of English texts.

GLiNER-BioMed is an efficient open NER model suite based on the GLiNER framework, specifically designed for the biomedical domain to recognize various types of biomedical entities.

This model is a fine-tuned version of roberta-base-biomedical-clinical-es on the CRAFT dataset, designed for named entity recognition in biomedical clinical texts.

This model is a DistilBERT model fine-tuned on the MIM-GOLD-NER dataset for Icelandic, designed to recognize named entities in Icelandic text.

A named entity recognition model fine-tuned based on the CAMeLBERT Arabic dialect model, supporting entity recognition in Arabic dialect texts