sequence-to-sequence-models 开源项目推荐（22 个）

awslabs /sockeye

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

uzaymacar /attention-mechanisms

Implementations for a family of attention mechanisms, suitable for all kinds of natural language processing tasks and compatible with TensorFlow 2.0 and Keras.

AILAB-CEFET-RJ /stconvs2s

论文《STConvS2S：用于天气预报的时空卷积序列到序列网络》（Elsevier，Neurocomputing）的代码

duyvuleo /Transformer-DyNet

An Implementation of Transformer (Attention Is All You Need) in DyNet

Heidelberg-NLP /SRL-S2S

Encoder-Decoder model for Semantic Role Labeling

AyanKumarBhunia /Handwriting-Trajectory-Recovery

Handwriting Trajectory Recovery using End-to-End Deep Encoder-Decoder Network, ICPR 2018.

SayamAlt /English-to-French-Language-Translation-using-Seq2Seq-Modeling

Established a deep learning model which can translate English words/sentences into their corresponding French translations.

SayamAlt /Abstractive-Text-Summarization-of-News-Articles

Successfully developed an encoder-decoder based sequence to sequence (Seq2Seq) model which can summarize the entire text of an Indian news summary into a short paragraph with limited number of words.

winston-lin-wei-cheng /Chunk-Level-Emotion-Retrieval

The proposed framework to retrieve the continuous chunk-level emotions via emo-rankers for Seq2Seq SER

robertocarlosmedina /attention-transformer-translator-1

Sequence to Sequence Transformer implementation in order to train a model to translate over Cap-verdian criole to English.

prashanthi-r /Eng-Hin-Neural-Machine-Translation

Sequence to sequence encoder-decoder model with Attention for Neural Machine Translation

srvk /jsalt-2018-grounded-s2s

Grounded Sequence-to-Sequence Transduction Team at JSALT 2018

yd1996 /NJUNMT-pytorch

该项目在 GitHub 上没有填写描述

ashokurlana /Neural-Machine-Translation

This repository shows the implementation of the paper Neural Machine Translation by Jointly Learning to Align and Translate

arpanjot-coding /Grammer-AI-corrector

A deep learning-based AI tool for correcting grammatical and spelling errors using TensorFlow. Features LSTM-based sequence-to-sequence modeling, data preprocessing, and real-time correction capabilities.

SayamAlt /CiteSum-Summarization-using-Seq2Seq-Attention

Successfully implemented a sequence-to-sequence text summarization model with attention mechanism to generate concise and context-aware abstractive summaries for citation-based academic texts from the CiteSum dataset, enabling efficient literature review and reference management.

SayamAlt /English-to-German-Translation-using-Seq2Seq

Successfully established a neural machine translation model using sequence to sequence modeling which can successfully translate English sentences to their corresponding German translations.

Mac0490 /Machine-Learning

Linear and generalized linear models for regression and classification, neural networks, Support Vector machines & kernel methods, mixture models & clustering. Program in Python. PyTorch & Tensorflow

aakanshadalmia /SumItUp

A concise summary generator for Amazon product reviews built using Transformers which maintains the original semantic essence and user sentiment

razamehar /Sentiment-Analysis-using-Deep-Learning---Machine-Learning

Sentiment analysis on the IMDB dataset using Bag of Words models (Unigram, Bigram, Trigram, Bigram with TF-IDF) and Sequence to Sequence models (one-hot vectors, word embeddings, pretrained embeddings like GloVe, and transformers with positional embeddings).