基于Transformer的单模型、多尺度的VAE模型

Last update: Aug 24, 2022

Related tags

Text Data & NLP univae

Overview

UniVAE

基于Transformer的单模型、多尺度的VAE模型

介绍

https://kexue.fm/archives/8475

依赖

需要大于0.10.6版本的bert4keras（当前还没有推到pypi上，可以直接从GitHub上clone最新版）。

引用

@misc{univae,
  title={UniVAE: Transformer-based Unified Variational Autoencoders},
  author={Jianlin Su},
  year={2021},
  howpublished={\url{https://github.com/bojone/univae}},
}

交流

QQ交流群：808623966，微信群请加机器人微信号spaces_ac_cn

Owner

苏剑林(Jianlin Su)

科学爱好者

GitHub Repository

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基于Transformer的单模型、多尺度的VAE模型

Related tags

Overview

UniVAE

介绍

依赖

引用

交流

Owner

苏剑林(Jianlin Su)

A method for cleaning and classifying text using transformers.

Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing

[ICLR 2021 Spotlight] Pytorch implementation for "Long-tailed Recognition by Routing Diverse Distribution-Aware Experts."

Modified GPT using average pooling to reduce the softmax attention memory constraints.

A sample project that exists for PyPUG's "Tutorial on Packaging and Distributing Projects"

Ongoing research training transformer language models at scale, including: BERT & GPT-2

A python package to fine-tune transformer-based models for named entity recognition (NER).

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch

Russian words synonyms and antonyms

Demo programs for the Talking Head Anime from a Single Image 2: More Expressive project.

Fuzzy String Matching in Python

Simple, Fast, Powerful and Easily extensible python package for extracting patterns from text, with over than 60 predefined Regular Expressions.

🧪 Cutting-edge experimental spaCy components and features

Part of Speech Tagging using Hidden Markov Model (HMM) POS Tagger and Brill Tagger

A fast, efficient universal vector embedding utility package.

A fast Text-to-Speech (TTS) model. Work well for English, Mandarin/Chinese, Japanese, Korean, Russian and Tibetan (so far). 快速语音合成模型，适用于英语、普通话/中文、日语、韩语、俄语和藏语（当前已测试）。

Facilitating the design, comparison and sharing of deep text matching models.

A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)

Machine learning models from Singapore's NLP research community

Pre-training BERT masked language models with custom vocabulary