langid.pyc
The modified version of langid.c
with Python bindings -- a straightforward replacement for langid.py
, offering the same features, but 200 times as faster.
Installation
pip install langid-pyc
Usage
Basic
from langid_pyc import (
classify,
rank,
)
classify("This is English text")
rank("This is English text")
Language set constraint
from langid_pyc import (
classify,
nb_classes,
set_languages,
)
nb_classes()
len(nb_classes())
set_languages(["en", "ru"])
nb_classes()
classify("This is English text")
classify("А это текст на русском")
set_languages()
len(nb_classes())
LanguageIdentifier
class
from langid_pyc import LanguageIdentifier
identifier = LanguageIdentifier.from_modelpath("ldpy3.pmodel")
len(identifier.nb_classes)
identifier.classify("This is English text")
How to build?
Install relevant protobuf
packages
apt install protobuf-c-compiler libprotobuf-c-dev
Install dev python requirements
pip install -r requirements.txt
Run build
make build
See Makefile for more details.
How to add a new model?
Train a new model using langid.py
package. You will get the model file as described here:
output_path = os.path.join(model_dir, 'your_new_model.model')
model = nb_ptc, nb_pc, nb_classes,tk_nextmove, tk_output
string = base64.b64encode(bz2.compress(cPickle.dumps(model)))
with open(output_path, 'w') as f:
f.write(string)
print "wrote model to %s (%d bytes)" % (output_path, len(string))
Move your_new_model.model
to models
dir and run
make your_new_model.model
Now you have your_new_model.pmodel
file in the root which can be feed to LanguageIdentifer.from_modelpath
from langid_pyc import LanguageIdentifier
your_new_identifier = LanguageIdentifier.from_modelpath("your_new_model.pmodel")
Benchmark
Benchmark was calculated on Mac M2 Max, 32Gb RAM with python 3.8.18 and can be found here.
TL;DR langid.pyc
is ~200x faster than langid.py
and ~1-1.5x faster than pycld2
, especially on long texts.
Original README
================
langid.c
readme
Introduction
langid.c
is an experimental implementation of the language identifier
described by [1] in pure C. It is largely based on the design of
langid.py
[2], and uses langid.py
to train models.
Planned features
See TODO
Speed
Initial comparisons against Google's cld2[3] suggest that langid.c
is about
twice as fast.
(langid.c) @mlui langid.c git:[master] wc -l wikifiles
28600 wikifiles
(langid.c) @mlui langid.c git:[master] time cat wikifiles | ./compact_lang_det_batch > xxx
cat wikifiles 0.00s user 0.00s system 0% cpu 7.989 total
./compact_lang_det_batch > xxx 7.77s user 0.60s system 98% cpu 8.479 total
(langid.c) @mlui langid.c git:[master] time cat wikifiles | ./langidOs -b > xxx
cat wikifiles 0.00s user 0.00s system 0% cpu 3.577 total
./langidOs -b > xxx 3.44s user 0.24s system 97% cpu 3.759 total
(langid.c) @mlui langid.c git:[master] wc -l rcv2files
20000 rcv2files
(langid.c) @mlui langid.c git:[master] time cat rcv2files | ./langidO2 -b > xxx
cat rcv2files 0.00s user 0.00s system 0% cpu 31.702 total
./langidO2 -b > xxx 8.23s user 0.54s system 22% cpu 38.644 total
(langid.c) @mlui langid.c git:[master] time cat rcv2files | ./compact_lang_det_batch > xxx
cat rcv2files 0.00s user 0.00s system 0% cpu 18.343 total
./compact_lang_det_batch > xxx 18.14s user 0.53s system 97% cpu 19.155 total
Model Training
Google's protocol buffers [4] are used to transfer models between languages. The
Python program ldpy2ldc.py
can convert a model produced by langid.py [2] into
the protocol-buffer format, and also the C source format used to compile an
in-built model directly into executable.
Dependencies
Protocol buffers [4]
protobuf-c [5]
Contact
Marco Lui saffsd@gmail.com
References
[1] http://aclweb.org/anthology-new/I/I11/I11-1062.pdf
[2] https://github.com/saffsd/langid.py
[3] https://code.google.com/p/cld2/
[4] https://github.com/google/protobuf/
[5] https://github.com/protobuf-c/protobuf-c