Commonly-used functions for building sequence labeling models.
Project description
SeqLbToolkit
This repo realizes Sequence Labeling Toolkits, a toolkit box containing useful functions for accelerating implementing sequences labeling deep learning models such as BiLSTM-CRF or BERT for Token Classification.
1. Installation
- Install from PyPI:
pip install -U SeqLbLoolkit
2. Documentation
Please refer to wiki for documentation.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
SeqLbToolkit-0.4.3.tar.gz
(25.8 kB
view details)
Built Distribution
File details
Details for the file SeqLbToolkit-0.4.3.tar.gz.
File metadata
- Download URL: SeqLbToolkit-0.4.3.tar.gz
- Upload date:
- Size: 25.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | cd1db656d3ec3ead326a312f20ffdd6cc4a0e501fe0f487508400caf877bb7a8 |
|
| MD5 | 436fc0c91a576427718e6730ff04b004 |
|
| BLAKE2b-256 | 1d89f958b09962f896b9d0ca9d9a79156089047a8d32dfeaebeb77c77b1ee300 |
File details
Details for the file SeqLbToolkit-0.4.3-py3-none-any.whl.
File metadata
- Download URL: SeqLbToolkit-0.4.3-py3-none-any.whl
- Upload date:
- Size: 30.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 9ab161138be6e18bba516c86cfc8d028879d8f96bdc28bb93fa586457fc08113 |
|
| MD5 | 8278d3752526aef13c6b39a9aab8a6f3 |
|
| BLAKE2b-256 | e67a08a8b37ea307bc8a9548e0be3397df6c03dae9852c44f2032884fd079b91 |
