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--- |
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license: apache-2.0 |
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tags: |
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- text-classification |
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- language-identification |
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library_name: fasttext |
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datasets: |
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- cis-lmu/GlotSparse |
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- cis-lmu/GlotStoryBook |
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metrics: |
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- f1 |
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--- |
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# GlotLID |
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## Description |
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GlotLID is a Fasttext language identification (LID) model for around 2000 languages. |
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### How to use |
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Here is how to use this model to detect the language of a given text: |
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```python |
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>>> import fasttext |
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>>> from huggingface_hub import hf_hub_download |
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>>> model_path = hf_hub_download(repo_id="cis-lmu/glotlid", filename="model.bin") |
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>>> model = fasttext.load_model(model_path) |
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>>> model.predict("Hello, world!") |
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``` |
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## License |
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The model is distributed under the Apache License, Version 2.0. |
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## Version |
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We always maintain the previous version of GlotLID in our repository. |
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To access a specific version, simply append the version number to the `filename`. |
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- For v1: `model_v1.bin` (introduced in the GlotLID paper and used in all experiments). |
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- For v2: `model_v2.bin` (an edited version of v1, featuring more languages, and cleaned from noisy corpora based on the analysis of v1). |
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`model.bin` always refers to the latest version (v2). |
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## References |
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If you use this model, please cite the following paper: |
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``` |
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@inproceedings{ |
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kargaran2023glotlid, |
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title={{GlotLID}: Language Identification for Low-Resource Languages}, |
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author={Kargaran, Amir Hossein and Imani, Ayyoob and Yvon, Fran{\c{c}}ois and Sch{\"u}tze, Hinrich}, |
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booktitle={The 2023 Conference on Empirical Methods in Natural Language Processing}, |
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year={2023}, |
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url={https://openreview.net/forum?id=dl4e3EBz5j} |
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} |
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``` |
