Pytorch Implementation of the Multi-task Neural Machine Transliteration System
Project description
Multi-task-NMT
The Pytorch-based implementation of the Multi-task Neural Machine Transliteration system initially built for the undegraduate thesis at University of Edinburgh.
- Requirements
torchtext>=0.5.0
torchvision>=0.5.0
python-Levenshtein>=0.12.0 # for Minimum Edit Distance
pandas>=1.0.3
- Install package
pip install multi-nmt-lawhy
Project details
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 Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file multi_task_nmt_lawhy-0.1.3-py3-none-any.whl.
File metadata
- Download URL: multi_task_nmt_lawhy-0.1.3-py3-none-any.whl
- Upload date:
- Size: 2.8 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
137fcd6cd3b55572113815b9ddb8111c93b3c9c4def649a84b51675552382858
|
|
| MD5 |
1f385ad2710d2ac7a220138b3e5c7094
|
|
| BLAKE2b-256 |
38d7450264bfe88fa7af8bfcca7ef36d319df8610150452e8a1b7fd1ad72bbea
|