| Name | fasttext-parallel JSON |
| Version |
0.1.4
JSON |
| download |
| home_page | |
| Summary | FastText Multithreading Inference |
| upload_time | 2023-01-30 14:20:08 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | |
| license | |
| keywords |
fasttext
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# 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
```
```python
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())
```
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"description": "# Multithreading For FastText\n\nAn easy to use tool for multithreading fasttext batch inference.\n\n## Features\n- Fast inference using multithreading utilizing all cpu cores.\n- Predicted labels are encoded as i16 numpy array for small memory footprint and easy serialization.\n\n## Performance\n\nOn macbook Air M2 chip, the performance is about 4 times faster,\nwhich is reasonable since it has 4 performance cores.\n\n```\n\u276f python -m unittest discover test\nfasttext-parallel 1.7130832079565153s\nfasttext 6.7440170829650015s\n```\n\n## Usage\n\n```\npip install fasttext-parallel\n```\n\n```python\nimport fasttext_parallel as ft\nmodel = ft.load_model(\"./model/lid.176.bin\")\n\n# this uses multiple threads\nlabels, probabilities = model.batch([\"\u4f60\u597d\", \"how are you\"])\n\n# labels are in a format of numpy.ndarray (i16) format\n# to get actual label, call get_label_by_id\nassert model.get_label_by_id(labels[0][0]) == \"__label__zh\"\nassert model.get_label_by_id(labels[1][0]) == \"__label__en\"\n\n# to view all labels (a dict from label_id to label)\nprint(model.get_labels())\n```\n\n",
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