fasttext-parallel

FastText Multithreading Inference

0.1.4

PyPI

Maintainers: 1

Multithreading For FastText

An easy to use tool for multithreading fasttext batch inference.

Features

Fast inference using multithreading utilizing all cpu cores.
Predicted labels are encoded as i16 numpy array for small memory footprint and easy serialization.

Performance

On macbook Air M2 chip, the performance is about 4 times faster, which is reasonable since it has 4 performance cores.

❯ python -m unittest discover test
fasttext-parallel 1.7130832079565153s
fasttext          6.7440170829650015s

Usage

pip install fasttext-parallel

import fasttext_parallel as ft
model = ft.load_model("./model/lid.176.bin")

# this uses multiple threads
labels, probabilities = model.batch(["你好", "how are you"])

# labels are in a format of numpy.ndarray (i16) format
# to get actual label, call get_label_by_id
assert model.get_label_by_id(labels[0][0]) == "__label__zh"
assert model.get_label_by_id(labels[1][0]) == "__label__en"

# to view all labels (a dict from label_id to label)
print(model.get_labels())

Keywords

fasttext

FAQs

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