Skip to main content

fastText

fastText is a library for efficient learning of word representations and sentence classification.

Requirements

fastText builds on modern Mac OS and Linux distributions. Since it uses C++11 features, it requires a compiler with good C++11 support. These include :

  • (gcc-4.8 or newer) or (clang-3.3 or newer)

You will need

Building fastText

The easiest way to get the latest version of fastText is to use pip.

$ pip install fasttext

If you want to use the latest unstable release you will need to build from source using setup.py.

Now you can import this library with

import fastText

Examples

In general it is assumed that the reader already has good knowledge of fastText. For this consider the main README and in particular the tutorials on our website.

We recommend you look at the examples within the doc folder.

As with any package you can get help on any Python function using the help function.

For example

+>>> import fastText
+>>> help(fastText.FastText)

Help on module fastText.FastText in fastText:

NAME
    fastText.FastText

DESCRIPTION
    # Copyright (c) 2017-present, Facebook, Inc.
    # All rights reserved.
    #
    # This source code is licensed under the MIT license found in the
    # LICENSE file in the root directory of this source tree.

FUNCTIONS
    load_model(path)
        Load a model given a filepath and return a model object.

    tokenize(text)
        Given a string of text, tokenize it and return a list of tokens
[...]

IMPORTANT: Preprocessing data / enconding conventions

In general it is important to properly preprocess your data. In particular our example scripts in the root folder do this.

fastText assumes UTF-8 encoded text. All text must be unicode for Python2 and str for Python3. The passed text will be encoded as UTF-8 by pybind11 before passed to the fastText C++ library. This means it is important to use UTF-8 encoded text when building a model. On Unix-like systems you can convert text using iconv.

fastText will tokenize (split text into pieces) based on the following ASCII characters (bytes). In particular, it is not aware of UTF-8 whitespace. We advice the user to convert UTF-8 whitespace / word boundaries into one of the following symbols as appropiate.

  • space

  • tab

  • vertical tab

  • carriage return

  • formfeed

  • the null character

The newline character is used to delimit lines of text. In particular, the EOS token is appended to a line of text if a newline character is encountered. The only exception is if the number of tokens exceeds the MAX_LINE_SIZE constant as defined in the Dictionary header. This means if you have text that is not separate by newlines, such as the fil9 dataset, it will be broken into chunks with MAX_LINE_SIZE of tokens and the EOS token is not appended.

The length of a token is the number of UTF-8 characters by considering the leading two bits of a byte to identify subsequent bytes of a multi-byte sequence. Knowing this is especially important when choosing the minimum and maximum length of subwords. Further, the EOS token (as specified in the Dictionary header) is considered a character and will not be broken into subwords.

Metadata

Release files for fasttext-github 0.8.22

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for fasttext-github 0.8.22
File Size Uploaded Provenance Actions
fasttext-github-0.8.22.tar.gz 48.9 kB Without provenance Details for fasttext-github-0.8.22.tar.gz

Release files / fasttext-github-0.8.22.tar.gz

Download URL fasttext-github-0.8.22.tar.gz
Size 48.9 kB
Tags Source
SHA-256 checksum
How to use checksums
f7750cbc964dd03720d9903608f49a8c8febefd8afb28d6fbaa0dd7f729af87a
BLAKE2b-256 checksum
How to use checksums
9562725d6cbaca8cd222b8ea008531fabbe724c4a5fa08907b7cf940bb67e35a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.3

Security for fasttext-github 0.8.22

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.8.22 This release

1 release file No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page