#Seq2seq
Showing 42 of 42 repositories tagged #seq2seq, ranked by stars
A neural network that transforms a design mock-up into a static website.
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
Play couplet with seq2seq model. 用深度学习对对联。
Automatic Speech Recognition (ASR), Speaker Verification, Speech Synthesis, Text-to-Speech (TTS), Language Modelling, Singing Voice Synthesis (SVS), Voice Conversion (VC)
My tensorflow implementation of "A neural conversational model", a Deep learning based chatbot
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.
텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다
CakeChat: Emotional Generative Dialog System
DELTA is a deep learning based natural language and speech processing platform. LF AI & DATA Projects: https://lfaidata.foundation/projects/delta/
Toolkit for efficient experimentation with Speech Recognition, Text2Speech and NLP
An elegent pytorch implement of transformers
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)
Simple implementations of NLP models. Tutorials are written in Chinese on my website https://mofanpy.com
tfts: Time Series Deep Learning Models in TensorFlow
Deep research agent to help you find the best GitHub repositories 🕵️!
Neural conversational model in Torch
Sequence to Sequence Models with PyTorch
Minimal Seq2Seq model with Attention for Neural Machine Translation in PyTorch
Multiple implementations for abstractive text summurization , using google colab
Sequence-to-Sequence learning using PyTorch
Sequence to sequence learning using TensorFlow.
中文聊天机器人，基于10万组对白训练而成，采用注意力机制，对一般问题都会生成一个有意义的答复。已上传模型，可直接运行。
Komputation is a neural network framework for the Java Virtual Machine written in Kotlin and CUDA C.
🏖 Easy training and deployment of seq2seq models.
Seq2SeqSharp is a tensor based fast & flexible deep neural network framework written by .NET (C#). It has many highlighted features, such as automatic differentiation, different network types (Transformer, LSTM, BiLSTM and so on), multi-GPUs supported, cross-platforms (Windows, Linux, MacOS), multimodal model for text and images and so on.
텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)
This is my reading list for my PhD in AI, NLP, Deep Learning and more.
A sequence2sequence chatbot implementation with TensorFlow.
Efficient Attention for Long Sequence Processing
GenieNLP: A versatile codebase for any NLP task
classy is a simple-to-use library for building high-performance Machine Learning models in NLP.
PyTorch Implementation of NBA game summary generator.
Customer support chatbot based on seq2seq model.
Exploring Neural Text Simplification
A numpy implementation of the Transformer model in "Attention is All You Need"
This repository holds files for the simple chatbot wrote in TensorFlow 1.4, with attention mechanism and bucketing.
Interesting python codes to tackle simple machine/deep learning tasks
Native and Private ML inference engine, embeddings, classification, reranking, search, and text generation. Rust core with C# bindings. No Python, no ONNX, no CUDA.