Discover qf6101/multi-label-bert-classification Open Source project

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Python
Created almost 5 years ago
Updated almost 5 years ago

qf6101

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Multi-label Bert Classification with focal loss weighting, auto cross-label data synthesis, adding exclude loss part among specific labels, upsampling, robust mean over all positive or negative loss, generating very fast inference-time model, etc.

topwords

Implementation of paper: Deng K, Bol P K, Li K J, et al. On the unsupervised analysis of domain-specific Chinese texts[J]. Proceedings of the National Academy of Sciences, 2016: 201516510.

Scala

multinomial-factorization-machines

Multinomial Factorization Machines

Terra

tensorflow_serving_examples

MNIST Java Client of tensorflow serving example 'https://tensorflow.github.io/serving/serving_basic'

Protocol Buffer

technical-skill-summary

My technical skill summary

Python

rmisdk

做算法的同学常常需要将做好的算法包装成服务，接受业务端请求，返回计算结果。RMISDK的目标是简化算法服务的上线过程，提供快速、稳定、可扩展的长连接服务。

Java

algorithm-components

This library was designed for high performance pipeline of feature transform and model prediction as a consistent solution for both online and offline scenes.

C++

preprocess_tabular_data

Auto inspect tabular data and transform data with PMML

Python

tensorflow_highlevelapi_example

Tensorflow high level API example

Python

qf6101/multi-label-bert-classification

qf6101

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