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FastText

28
54
+ 1
1
Flair

14
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1
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Flair vs FastText: What are the differences?

What is Flair? A simple framework for natural language processing. 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.

What is FastText? Library for efficient text classification and representation learning. It is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices.

Flair and FastText can be primarily classified as "NLP / Sentiment Analysis" tools.

Flair is an open source tool with 7.21K GitHub stars and 791 GitHub forks. Here's a link to Flair's open source repository on GitHub.

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Pros of FastText
Pros of Flair
  • 1
    Simple
  • 1
    Open Source

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Cons of FastText
Cons of Flair
  • 1
    No step by step API support
  • 1
    No in-built performance plotting facility or to get it
  • 1
    No step by step API access
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    What is FastText?

    It is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices.

    What is Flair?

    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.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use FastText?
    What companies use Flair?
    See which teams inside your own company are using FastText or Flair.
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    What tools integrate with FastText?
    What tools integrate with Flair?
    What are some alternatives to FastText and Flair?
    TensorFlow
    TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
    Gensim
    It is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community.
    SpaCy
    It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
    rasa NLU
    rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.
    Amazon Comprehend
    Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to discover insights from text. Amazon Comprehend provides Keyphrase Extraction, Sentiment Analysis, Entity Recognition, Topic Modeling, and Language Detection APIs so you can easily integrate natural language processing into your applications.
    See all alternatives