seq2seq

A neural network that transforms a design mock-up into a static website.

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

Play couplet with seq2seq model. 用深度学习对对联。

Lingvo

Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.

Large Concept Models: Language modeling in a sentence representation space

Awesome Chatbot Projects,Corpus,Papers,Tutorials.Chinese Chatbot =>:

An elegent pytorch implement of transformers

:art: 数学公式识别增强版：中英文手写印刷公式、支持初级符号推导（数据结构基于 LaTeX 抽象语法树）Math Formula OCR Pro, supports handwrite, Chinese-mixed formulas and simple symbol reasoning (based on LaTeX AST).

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

Sequence-to-sequence framework with a focus on Neural Machine Translation based on PyTorch

💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️

This series will take you on a journey from the fundamentals of NLP and Computer Vision to the cutting edge of Vision-Language Models.

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。

1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems.

Source code for end-to-end dialogue model from the MultiWOZ paper (Budzianowski et al. 2018, EMNLP)

Deep research agent to help you find the best GitHub repositories 🕵️!

tfts: Time Series Deep Learning Models in TensorFlow

多标签文本分类，多标签分类，文本分类, multi-label, classifier, text classification, BERT, seq2seq，attention, multi-label-classification

Minimalist NMT for educational purposes

Minimal Seq2Seq model with Attention for Neural Machine Translation in PyTorch