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PyPI · #2882 most downloaded on PyPI
fasttext Python bindings
Last release 2 years ago
no release in 18 months
Ships unpredictably
gaps range from 8 days to 4.1 years
Rarely documented
notes for 3 of 36 stable releases
Nothing withdrawn
no release was ever pulled
10 years old
36 releases · first in 2016
Nothing published for this version
We are happy to announce the release of version 0.9.2.
We are happy to announce the release of version 0.9.2.
We are excited to release fastText bindings for WebAssembly. Classification tasks are widely used in web applications and we believe giving access to the complete fastText API from the browser will notably help our community to build nice tools. See our documentation to learn more.
Finding the best hyperparameters is crucial for building efficient models. However, searching the best hyperparameters manually is difficult. This release includes the autotune feature that allows you to find automatically the best hyperparameters for your dataset.
You can find more information on how to use it here.
fastText loves Python. In this release, we have:
The autotune feature is fully integrated with our Python API. This allows us to have a more stable autotune optimization loop from Python and to synchronize the best hyper-parameters with the _FastText model object.
We release two helper scripts:
They can also be used directly from our Python API.
When you test a trained model, you can now have more detailed results for the precision/recall metrics of a specific label or all labels.
This release contains the source code of the unsupervised multilingual alignment paper.
We want to thank our community for giving us feedback on Facebook and on GitHub.
One column per quarter.
We are happy to announce the release of version 0.9.1.
We are happy to announce the release of version 0.9.1.
The main goal of this release is to merge two existing python modules: the official fastText module which was available on our github repository and the unofficial fasttext module which was available on pypi.org.
You can find an overview of the new API here, and more insight in our blog post.
This version includes a massive rewrite of internal classes. The training and test are now split into three different classes : Model that takes care of the computational aspect, Loss that handles loss and applies gradients to the output matrix, and State that is responsible of holding the model's state inside each thread.
That makes the code more straighforward to read but also gives a smaller memory footprint, because the data needed for loss computation is now hold only once unlike before where there was one for each thread.
on_unicode_error argument that helps to handle unicode issues one can face with some datasetspy::str class between python2 and python3aws to fbaipublicfilesAs always, we want to thank you for your help and your precious feedback which helps making this project better.
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It is still compatible with older versions of the class, but some methods are now marked as deprecated and will probably be removed in the next releas…
We are happy to announce the change of the license from BSD+patents to MIT and the release of fastText 0.2.0.
The main purpose of this release is to set a beta C++ API of the FastText class. The class now behaves as a computational library: we moved the display and some usage error handlings outside of it (mainly to main.cc and fasttext_pybind.cc). It is still compatible with older versions of the class, but some methods are now marked as deprecated and will probably be removed in the next release.
In this respect, we also introduce the official support for python. The python binding of fastText is a client of the FastText class.
Here is a short summary of the 104 commits since 0.1.0 :
-loss ova or -loss one-vs-all command line option ( 8850c51b972ed68642a15c17fbcd4dd58766291d ).FastText class ( 256032b87522cdebc4850c99b204b81b3255cb2a ).setup.py OS X compiler flags, pybind11 include.README.mdMakefile and setup.py in order to build for measuring the coverage.We want to thank you all for being a part of this community and sharing your passion with us. Some of these improvements would not have been possible without your help.
Summary: Re-licensing fastText to MIT
Reviewed By: piotr-bojanowski
Differential Revision: D13415080
fbshipit-source-id: 6708849531fe7559cde273a3024660bc8b3b3750
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