|
--- |
|
license: apache-2.0 |
|
tags: |
|
- text-classification |
|
- language-identification |
|
library_name: fasttext |
|
datasets: |
|
- cis-lmu/GlotSparse |
|
- cis-lmu/GlotStoryBook |
|
metrics: |
|
- f1 |
|
--- |
|
|
|
|
|
# GlotLID |
|
|
|
## Description |
|
|
|
GlotLID is a Fasttext language identification (LID) model for around 2000 languages. |
|
|
|
|
|
### How to use |
|
|
|
Here is how to use this model to detect the language of a given text: |
|
|
|
```python |
|
>>> import fasttext |
|
>>> from huggingface_hub import hf_hub_download |
|
|
|
>>> model_path = hf_hub_download(repo_id="cis-lmu/glotlid", filename="model.bin") |
|
>>> model = fasttext.load_model(model_path) |
|
>>> model.predict("Hello, world!") |
|
|
|
``` |
|
|
|
## License |
|
|
|
The model is distributed under the Apache License, Version 2.0. |
|
|
|
## References |
|
|
|
If you use this model, please cite the following paper: |
|
|
|
``` |
|
@inproceedings{ |
|
kargaran2023glotlid, |
|
title={{GlotLID}: Language Identification for Low-Resource Languages}, |
|
author={Kargaran, Amir Hossein and Imani, Ayyoob and Yvon, Fran{\c{c}}ois and Sch{\"u}tze, Hinrich}, |
|
booktitle={The 2023 Conference on Empirical Methods in Natural Language Processing}, |
|
year={2023}, |
|
url={https://openreview.net/forum?id=dl4e3EBz5j} |
|
} |
|
|
|
``` |
