Text Tagging Model
Here we collected some online and offline models for text tagging.
🚀 Demo
https://colab.research.google.com/drive/1xlevLnqxd_wCtXunGgf_pSrdkz85jt49?usp=sharing
🧐 Features
Here're some of the project's best features:
- Online model: Rake Based Model with 10-20 it/sec
- Offline models: Bart based model with summarisation or attention. 1-5 it/sec
🛠️ Installation Steps:
1. Installation
pip install text-tagging-model
2. import
from text_tagging_model.models.rake_based_model import TagsExtractor
3. Init tagger
tagger = TagsExtractor()
4. Get tags
tagger.extract(some_text)
1 maintainer
Release files for text-tagging-model 0.1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| text_tagging_model-0.1.4.tar.gz | 8.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| text_tagging_model-0.1.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 25.0 kB
Release files / text_tagging_model-0.1.4.tar.gz
| Download URL | text_tagging_model-0.1.4.tar.gz |
|---|---|
| Size | 8.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.4.2 CPython/3.9.6 Darwin/23.3.0
|
Release files / text_tagging_model-0.1.4-py3-none-any.whl
| Download URL | text_tagging_model-0.1.4-py3-none-any.whl |
|---|---|
| Size | 16.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.4.2 CPython/3.9.6 Darwin/23.3.0
|
