Easy to use extractive text summarization with BERT

Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.

The PyTorch Implementation of SummaRuNNer

a contextual, biasable, word-or-sentence-or-paragraph extractive summarizer powered by the latest in text embeddings (Bert, Universal Sentence Encoder, Flair)

Lecture summarization with BERT

Datasets I have created for scientific summarization, and a trained BertSum model

Text summarization starting from scratch.

Abstractive and Extractive Text summarization using Transformers.

Automagically generates summaries from html or text.

Code and Data Repo for COLING'22 paper "Noise-injected Consistency Training and Entropy-constrained Pseudo Labeling for Semi-supervised Extractive Summarization"

Code for ACL 2022 paper on the topic of long document summarization: MemSum: Extractive Summarization of Long Documents Using Multi-Step Episodic Markov Decision Processes

Tensorflow implementation of SummaRuNNer

Let AI create the notes of your Teams Meeting

SUMPUBMED: Summarization Dataset of PubMed Scientific Article

Automatic generation of reviews of scientific papers

Source based extractive summarizer web-app and chatbot.

Use-cases of Hugging Face's BERT (e.g. paraphrase generation, unsupervised extractive summarization).

Ultra-fast, spookily accurate text summarizer that works on any language

A system capable of converting Nepali speech to text and generate summary of text

Scripts for an upcoming blog "Extractive vs. Abstractive Summarization" for RaRe Technologies.