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Flair vs SpaCy: What are the differences?

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; SpaCy: Industrial-Strength Natural Language Processing in Python. 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.

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

Flair is an open source tool with 6.53K GitHub stars and 666 GitHub forks. Here's a link to Flair's open source repository on GitHub.

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Pros of Flair
Pros of SpaCy
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    Open Source
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    No vendor lock-in

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Cons of Flair
Cons of SpaCy
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      Requires creating a training set and managing training

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