Metadata-Version: 2.1
Name: MultiEL
Version: 0.2
Summary: Multilingual Entity Linking model by BELA model
Home-page: https://github.com/wannaphong/MultiEL
Author: Wannaphong
Author-email: wannaphong@yahoo.com
License: MIT License
Project-URL: Source, https://github.com/wannaphong/MultiEL
Project-URL: Bug Reports, https://github.com/wannaphong/MultiEL/issues
Keywords: NLP,natural language processing,text analytics,text processing,localization,computational linguistics
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Text Processing
Classifier: Topic :: Text Processing :: General
Classifier: Topic :: Text Processing :: Linguistic
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: faiss-gpu
Requires-Dist: fairscale
Requires-Dist: hydra-core
Requires-Dist: hydra-submitit-launcher
Requires-Dist: pyyaml
Requires-Dist: pytorch-lightning
Requires-Dist: transformers
Requires-Dist: tqdm
Requires-Dist: sentencepiece
Requires-Dist: h5py
Requires-Dist: protobuf (==3.20)
Requires-Dist: ujson
Requires-Dist: huggingface-hub

# MultiEL
Multilingual Entity Linking model by BELA model

This project want to create easy-to-use Multilingual Entity Linking model by BELA model.

**Origin Project**

- Bi-encoder Entity Linking Architecture (BELA): [https://github.com/facebookresearch/BELA](https://github.com/facebookresearch/BELA)


## Install

> pip install multiel

## Usage

```python
from multiel import BELA

bela_run = BELA(device="cuda")

print(bela_run.process_batch(["นายกประยุทธ์ประกาศจัดการเลือกตั้ง"]))
```
