fastText
Library for efficient text classification and representation learning
FastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware and is designed to handle large text datasets efficiently. FastText is developed by Facebook's AI Research lab (FAIR) to provide state-of-the-art performance in text classification and representation learning.
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Domain Rating
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Domain Authority
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Citation Level
2016
English, etc
Website Key Features
Efficient text classification
FastText is optimized for speed and can train on more than a billion words in less than ten minutes using a standard multicore CPU.
Word representation learning
It provides tools to learn word representations (embeddings) that capture semantic and syntactic information.
Subword information
FastText uses character n-grams to capture the meaning of suffixes/prefixes and can generate better word embeddings for rare words.
Multi-label classification
Supports classification tasks where each input can belong to multiple categories simultaneously.
Language identification
Can quickly and accurately identify the language of a given text from a wide range of supported languages.
Pre-trained models
Offers pre-trained word vectors for many languages, facilitating quick start and application development.
Command line interface
Provides a simple command-line interface for training and testing models without the need for extensive programming knowledge.
Python bindings
Includes Python bindings for easy integration into Python-based projects and workflows.
Additional information
License
FastText is released under the MIT License, making it free for both academic and commercial use.
GitHub Repository
The source code and documentation are available on GitHub, encouraging community contributions and transparency.
Research Paper
The underlying algorithm and methodology are detailed in a research paper titled 'Bag of Tricks for Efficient Text Classification' by Joulin et al.
Community Support
FastText has a strong community support with active forums and discussion groups for troubleshooting and sharing best practices.
Integration
It can be integrated with other machine learning frameworks and tools, enhancing its utility in complex projects.
HTTP headers
Security headers report is a very important part of user data protection. Learn more about http headers for fasttext.cc