elsa

LightSeq: A High Performance Library for Sequence Processing and Generation

Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo

Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)

Easy to use extractive text summarization with BERT

TextGen: Implementation of Text Generation models, include LLaMA, BLOOM, GPT2, BART, T5, SongNet and so on. 文本生成模型，实现了包括LLaMA，ChatGLM，BLOOM，GPT2，Seq2Seq，BART，T5，UDA等模型的训练和预测，开箱即用。

Code for ACL 2018 paper: "Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting. Chen and Bansal"

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

Abstractive summarisation using Bert as encoder and Transformer Decoder

A Abstractive Summarization Implementation with Transformer and Pointer-generator

Pointer-generator reinforced seq2seq summarization in PyTorch