hmxv2 Goto Github PK

hmxv2.github.io

image_classification

image_classification_draft

learngit

mainpartextractor

主谓宾提取器的Java实现（对斯坦福的代码失去兴趣，不再维护）

milvus-sdk-java

Java SDK for Milvus.

mixpoet

Source codes of MixPoet: Diverse Poetry Generation via Learning Controllable Mixed Latent Space (AAAI 2020)

multi-sentence-compression

Lightweight method based on shortest path on word graphs and NLP to generate single sentence summaries that highly relevant and grammatically sound

multidocrpdsummarizer

nmt

opencv_contrib

Repository for OpenCV's extra modules

pylsa

Latent Semantic Analysis in Python

python-alibaba

使用python采集阿里巴巴(http://www.1688.com)百万商户信息简易版

pytorch-dual-learning

Implementation of Dual Learning NMT on PyTorch

pytorch-seq2seq

An open source framework for seq2seq models in PyTorch.

pytorch_nmt

A neural machine translation model in PyTorch

pytorch_rvae

Recurrent Variational Autoencoder that generates sequential data implemented with pytorch

rl4nmt

Reinforcement Learning for Neural Machine Translation

sentence-simplification-acl14

State-of-the-art Supervised Sentence Simplification System from ACL 2014

sentence-vae

PyTorch Implementation of "Generating Sentences from a Continuous Space" by Bowman et al 2015 https://arxiv.org/abs/1511.06349

seq2seq-pytorch

Sequence to Sequence Models with PyTorch

seq3

Source code for the NAACL 2019 paper "SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression"

strokewidthtransform

A playground implementing Epshtein, Ofek, and Wexler's Stroke Width Transform

takahe

takahe is a multi-sentence compression module

tensorboard_demo

text-segmentation

Implementation of the paper: Text Segmentation as a Supervised Learning Task

text_autoencoder

A RNN based Sequence to Sequence autoenconder for yelp reviews (sentences).

text_data_enhancement_with_lasertagger

Modify Chinese text, modified on LaserTagger Model. 文本复述，基于lasertagger做中文文本数据增强。

titanic

wmpoetry

Source codes of Chinese Poetry Generation with a Working Memory Model (IJCAI 2018)