BNTRANSLIT
BNTRANSLIT is a deep learning based transliteration app for Bangla word.
Installation
pip install bntranslit
Dependency
- pytorch 1.7.0 or 1.7.0+
NB: No GPU Needed. Totally CPU based
Pre-trained Model
Usage
from bntranslit import BNTransliteration
model_path = "bntranslit_model.pth"
bntrans = BNTransliteration(model_path)
word = "aami"
output = bntrans.predict(word, topk=10)
# output: ['আমি', 'আমী', 'অ্যামি', 'আমিই', 'এমি', 'আমির', 'আমিদ', 'আমই', 'আমে', 'আমিতে']
Datasets and Training Details
- We used Google Dakshina Dataset
- Thanks to AI4Bharat for providing training notebook with details explanation
- We trained Google Bangla Dakshina lexicons train datasets for 10 epochs with batch size 128, 1e-3, embedding dim = 300, hidden dim = 512, lstm, used attention
- We evaluated our trained model with Google Bangla Dakshina lexicon test data using AI4Bharat evaluation script and our evaluation results insides
docs/evaluation_summary.txt
Metadata
Release files for bntranslit 2.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| bntranslit-2.1.0.tar.gz | 8.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| bntranslit-2.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 16.9 kB
Release files / bntranslit-2.1.0.tar.gz
| Download URL | bntranslit-2.1.0.tar.gz |
|---|---|
| Size | 8.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
Release files / bntranslit-2.1.0-py3-none-any.whl
| Download URL | bntranslit-2.1.0-py3-none-any.whl |
|---|---|
| Size | 8.3 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.6.1 requests/2.24.0 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.8.5
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