#
Using Flair at Hugging Face

Flair is a very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends.

##
Exploring Flair in the Hub

You can find `flair` models by filtering at the left of the models page.

All models on the Hub come with these useful features:

1. An automatically generated model card with a brief description.
2. An interactive widget you can use to play with the model directly in the browser.
3. An Inference API that allows you to make inference requests.

##
Installation

To get started, you can follow the Flair installation guide. You can also use the following one-line install through pip:

    $ pip install -U flair

##
Using existing models

All `flair` models can easily be loaded from the Hub:

    from flair.data import Sentence
    from flair.models import SequenceTagger

    # load tagger
    tagger = SequenceTagger.load("flair/ner-multi")

Once loaded, you can use `predict()` to perform inference:

    sentence = Sentence("George Washington ging nach Washington.")
    tagger.predict(sentence)

    # print sentence
    print(sentence)

It outputs the following:

    Sentence[6]: "George Washington ging nach Washington." → ["George Washington"/PER, "Washington"/LOC]

If you want to load a specific Flair model, you can click `Use in Flair` in the model card and you will be given a working snippet!

##
Additional resources

- Flair repository
- Flair docs
- Official Flair models on the Hub (mainly trained by @alanakbik and @stefan-it)

Update on GitHub