smiles-featurizers

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.