Sudachi C Imitator Transformers
This package imitates Japanese morphological analysis of Sudachi SplitMode.C and SudachiDict-full with a small transformers model.
You can add tokenization and part-of-speech estimation to your environment
with only 4MB additoinal disk space if you already have transrofmers in your environment.
Installation
$ pip install sudachi_c_imitator_transformers
Usage Examples
>>> import sudachi_c_imitator_transformers
>>> tagger = sudachi_c_imitator_transformers.Tagger()
>>> sample_text = '使い方のサンプルです。'
>>> tagger.parse(sample_text)
[('使い方', '名詞'), ('の', '助詞'), ('サンプル', '名詞'), ('です', '助動詞'), ('。', '補助記号')]
Input string length must be 256 or less.
Release files for sudachi-c-imitator-transformers 0.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sudachi_c_imitator_transformers-0.2.1.tar.gz | 2.2 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sudachi_c_imitator_transformers-0.2.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.3 MB
Release files / sudachi_c_imitator_transformers-0.2.1.tar.gz
| Download URL | sudachi_c_imitator_transformers-0.2.1.tar.gz |
|---|---|
| Size | 2.2 MB |
| Tags | Source |
|
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Release files / sudachi_c_imitator_transformers-0.2.1-py3-none-any.whl
| Download URL | sudachi_c_imitator_transformers-0.2.1-py3-none-any.whl |
|---|---|
| Size | 2.2 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Uploaded via |
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