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flair

A very simple framework for state-of-the-art Natural Language Processing (NLP)

Flair is:

  • A powerful NLP library. Flair allows you to apply our state-of-the-art natural language processing (NLP)
    models to your text, such as named entity recognition (NER), part-of-speech tagging (PoS),
    sense disambiguation and classification.

  • Multilingual. Thanks to the Flair community, we support a rapidly growing number of languages. We also now include
    one model, many languages‘ taggers, i.e. single models that predict PoS or NER tags for input text in various languages.

  • A text embedding library. Flair has simple interfaces that allow you to use and combine different word and
    document embeddings, including our proposed Flair embeddings, BERT embeddings and ELMo embeddings.

  • A Pytorch NLP framework. Our framework builds directly on Pytorch, making it easy to
    train your own models and experiment with new approaches using Flair embeddings and classes.

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fairseq

fairseq 是一个序列建模工具包,允许研究人员和开发人员为翻译、摘要、语言建模和其他文本生成任务培训自定义模型。它提供了各种序列到序列模型的参考实现。

Machine translation

Machine translation is the task of translating a sentence in a source language to a different target language.

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按顺序必读官方指引 TensorFlow Datasets and Estimators

标题 说明 时间
Introduction to TensorFlow Datasets and Estimators Google Develops Blog Part 1 2017-09-12
Introducing TensorFlow Feature Columns Google Develops Blog Part 2 2017-11-20
Creating Custom Estimators in TensorFlow Google Develops Blog Part 3 2017-12-19
Classifying text with TensorFlow Estimators Part 4 2018-03-07
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