Skip to main content

BERT Application

Project description

BAND:BERT Application aNd Deployment

A simple and efficient BERT model training and deployment framework.

Contributors Forks Stargazers Issues MIT License



BAND:BERT Application aNd Deployment
探索本项目的文档 »

查看Demo · 报告Bug · 提出新特性 · 问题交流

What is it

Encoding/Embedding is a upstream task of encoding any inputs in the form of text, image, audio, video, transactional data to fixed length vector. Embeddings are quite popular in the field of NLP, there has been various Embeddings models being proposed in recent years by researchers, some of the famous one are bert, xlnet, word2vec etc. The goal of this repo is to build one stop solution for all embeddings techniques available, here we are starting with popular text embeddings for now and later on we aim to add as much technique for image, audio, video inputs also.
Finally, embedding-as-service help you to encode any given text to fixed length vector from supported embeddings and models.

💾 Installation

▴ Back to top

Install the band via pip.

$ pip install band -U

Note that the code MUST be running on Python >= 3.6. Again module does not support Python 2!

⚡ ️Getting Started

▴ Back to top


For more information about dataset, see

Dataset Name Language TASK Description
ChnSentiCorp CN Text Classification Binary Classification
LCQMC CN Question Answer Match Binary Classification
MSRA_NER CN Named Entity Recognition Sequence Labeling
Toxic EN Text Classification Multi-label Multi-label
Thucnews CN Text Classification Multi-class Classification
SQUAD EN Machine Reading Comprehension Span
DRCD CN Machine Reading Comprehension Span
CMRC CN Machine Reading Comprehension Span

Current Pretrained Models

For more information about pretrained models, see

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

band-0.3.3.tar.gz (33.1 kB view hashes)

Uploaded Source

Built Distribution

band-0.3.3-py3-none-any.whl (42.4 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page