xlnet

Awesome Pretrained Chinese NLP Models，高质量中文预训练模型&大模型&多模态模型&大语言模型集合

Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow. This is part of the CASL project: http://casl-project.ai/

🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.

A curated list of NLP resources focused on Transformer networks, attention mechanism, GPT, BERT, ChatGPT, LLMs, and transfer learning.

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。

Official implementation of the papers "GECToR – Grammatical Error Correction: Tag, Not Rewrite" (BEA-20) and "Text Simplification by Tagging" (BEA-21)

This repo contains a PyTorch implementation of a pretrained BERT model for multi-label text classification.

Annotations of the interesting ML papers I read

Transformer Architectures for Generative AI

Scripts and Approach for Amazon ML Challenge

Absolutely amazing SOTA Google Colab (Jupyter) Notebooks for creating/training SOTA Music AI models and for generating music with Transformer technology (Google XLNet/Transformer-XL)

Abstractive and Extractive Text summarization using Transformers.

Distilling Task-Specific Knowledge from Teacher Model into BiLSTM

Comparing state of the art models for text summary generation

Sarcasm is a term that refers to the use of words to mock, irritate, or amuse someone. It is commonly used on social media. The metaphorical and creative nature of sarcasm presents a significant difficulty for sentiment analysis systems based on affective computing. The technique and results of our team, UTNLP, in the SemEval-2022 shared task 6 on sarcasm detection are presented in this paper.

An automated solution for fact-checking using available claims and fake-news datasets to fine-tune state-of-the-art language models published recently for NLP tasks (BERT, RoBERTa, XLNet, ConvBERT...) in order to classify unseen claims.