Popular GitHub Repositories for Bart

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,...)

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。

Multilingual/multidomain question generation datasets, models, and python library for question generation.

Build and train state-of-the-art natural language processing models using BERT

code for AAAI2022 paper "Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification"

Calculate perplexity on a text with pre-trained language models. Support MLM (eg. DeBERTa), recurrent LM (eg. GPT3), and encoder-decoder LM (eg. Flan-T5).

Code associated with the "Data Augmentation using Pre-trained Transformer Models" paper

Automated Categorization: Utilizing the power of neural networks, this project offers an automated solution to categorize bank descriptions, reducing manual effort and enhancing efficiency while maintaining privacy.

NAACL 2021 - Progressive Generation of Long Text

Official implementation of the paper "IteraTeR: Understanding Iterative Revision from Human-Written Text" (ACL 2022)

Codes for our paper "JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs" (ACL 2021 Findings)

Code for EMNLP 2021 paper "Topic-Aware Contrastive Learning for Abstractive Dialogue Summarization"

The first-ever vast natural language generation benchmark for Indonesian, Sundanese, and Javanese. We provide multiple downstream tasks, pre-trained IndoGPT and IndoBART models, and a starter code! (EMNLP 2021)

A tool to automatically summarize documents abstractively using the BART or PreSumm Machine Learning Model.

TrAVis: Visualise BERT attention in your browser

Code associated with the "Data Augmentation using Pre-trained Transformer Models" paper

Implement Question Generator with SOTA pre-trained Language Models (RoBERTa, BERT, GPT, BART, T5, etc.)

An English-to-Cantonese machine translation model