# Case Insensitive

This model is an Indonesian text summarization model based on the PEGASUS architecture, fine-tuned on the Indosum, Liputan6, and XLSum datasets, suitable for news text summarization tasks.

RadBERT is a radiology-specific BERT model initialized from BioBERT and continuously pre-trained on radiology report data, suitable for natural language processing tasks in biomedical and radiology fields.

A named entity recognition model fine-tuned based on the SciBERT pre-trained model for scientific domains

An English named entity recognition model fine-tuned on the conll2003 dataset based on roberta-large, specifically optimized for recognizing entities with non-initial capital letters

This model is obtained through distillation from a zero-shot classification pipeline for AG News, primarily demonstrating how to distill an expensive zero-shot model into a more efficient student model.

A BERT base model pretrained on Indonesian Wikipedia using Masked Language Modeling (MLM) objective, case insensitive.

A lightweight named entity recognition model based on DistilBERT, optimized for English text and case-insensitive.

IndoBERT is a state-of-the-art language model developed for Indonesian based on the BERT architecture, trained using Masked Language Modeling (MLM) and Next Sentence Prediction (NSP) objectives.

PERT is a pre-trained language model based on the BERT architecture, supporting English task processing.

This is a BERT-based Indonesian pretrained model trained on Wikipedia and newspaper data, suitable for various natural language processing tasks.

IndoBERT is a BERT model variant tailored for the Indonesian language, trained using masked language modeling and next sentence prediction objectives. The Lite version is a lightweight model suitable for resource-constrained environments.

This is a Danish pre-trained BERT model developed by Certainly (formerly BotXO), later fine-tuned by Malte Højmark-Bertelsen on the DaNE dataset for named entity recognition tasks.