Please cite 1 if using this code for learning word representations or 2 if using for text classification. (Word-representation modes skipgram and cbow use a default -minCount of 5.) References qnorm quantizing the norm separately ĭefaults may vary by mode. retrain finetune embeddings if a cutoff is applied cutoff number of words and ngrams to retain The following arguments for quantization are optional: saveOutput whether output params should be saved pretrainedVectors pretrained word vectors for supervised learning lrUpdateRate change the rate of updates for the learning rate The following arguments for training are optional: ![]() minCountLabel minimal number of label occurrences minCount minimal number of word occurrences The following arguments for the dictionary are optional: You might want to use this if you are a developer or power-user. There is also the master branch that contains all of our most recent work, but comes along with all the usual caveats of an unstable branch. You can find our latest stable release in the usual place. We discuss building the latest stable version of fastText. Then, with those set, the next FINDPACKAGE (CURL) will 'find' CURL because. By default it is empty, it is intended to be set by the project. If these requirements make it impossible for you to use fastText, please open an issue and we will try to accommodate you. CMAKELIBRARYPATH Semicolon-separated list of directories specifying a search path for the findlibrary command. One of the oldest distributions we successfully built and tested the Python bindings under is Debian jessie. One of the oldest distributions we successfully built and tested the CLI under is Debian jessie.įor the word-similarity evaluation script you will need:įor the python bindings (see the subdirectory python) you will need: If you want to use cmake you need at least version 2.8.9. (g++-4.7.2 or newer) or (clang-3.3 or newer)Ĭompilation is carried out using a Makefile, so you will need to have a working make.Since it uses some C++11 features, it requires a compiler with good C++11 support. Generally, fastText builds on modern Mac OS and Linux distributions. We are continuously building and testing our library, CLI and Python bindings under various docker images using circleci. We also provide a cheatsheet full of useful one-liners. You can find answers to frequently asked questions on our website. The preprocessed YFCC100M data used in.Models for language identification and various supervised tasks.Word vectors for 157 languages trained on Wikipedia and Crawl.Recent state-of-the-art English word vectors.FastText.zip: Compressing text classification models.Bag of Tricks for Efficient Text Classification.Enriching Word Vectors with Subword Information. ![]()
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