This repository provides the PyTorch implementation of BioBERT. You can easily use BioBERT with transformers. This project is supported by the members of DMIS-Lab @ Korea University including Jinhyuk Lee, Wonjin Yoon, Minbyul Jeon
SentAugment is a data augmentation technique for NLP that retrieves similar sentences from a large bank of sentences. It can be used in combination with self-training and knowledge-distillation, or for retrieving paraphrases.
FinBERT is a BERT model pre-trained on financial communication text. The purpose is to enhance finaincal NLP research and practice. It is trained on the following three finanical communication corpus. The total corpora size is 4.9
This respository contains the dataset used in "Open Table-and-Text Question Answering" and the baseline code for the dataset (OTT-QA). This dataset contains open questions which require retrieving tables and text from the web to a
BERTopic is a topic modeling technique that leverages BERT embeddings and c-TF-IDF to create dense clusters allowing for easily interpretable topics whilst keeping important words in the topic descriptions.
MadNLP is a nonlinear programming (NLP) solver, purely implemented in Julia. MadNLP implements a filter line-search algorithm, as that used in Ipopt. MadNLP seeks to streamline the development of modeling and algorithmic paradigms