BaselMousi
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README.md
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---
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license: cc-by-4.0
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---
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license: cc-by-4.0
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base_model:
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- facebook/nllb-200-3.3B
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pipeline_tag: translation
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---
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# AraDiCE-msa-to-egy: An MSA to Egyptian Machine Translation model based on NLLB-3.3B
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This repository includes an MSA to Egyptian machine translation model that was finetuned based on nllb-3.3B. The model was used to curate benchmarks for the AraDiCE paper (citation below). The The human post-edited benchmarks can be found<a href="https://huggingface.co/datasets/QCRI/AraDiCE" target="_blank" style="margin-right: 15px; margin-left: 10px">here.</a>
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## Sample Usage
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```python
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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tokenizer = AutoTokenizer.from_pretrained("QCRI/AraDiCE-msa-to-egy")
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model = AutoModelForSeq2SeqLM.from_pretrained("QCRI/AraDiCE-msa-to-egy")
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article = "من مصلحتك أن ترحل من كازابلانكا لفترة. هناك موقع لفرنسا الحرة بالقرب من برازفيل. قد أسهل لك العبور."
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inputs = tokenizer(article, return_tensors="pt")
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translated_tokens = model.generate(
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**inputs, forced_bos_token_id=tokenizer.convert_tokens_to_ids("arz_Arab"), max_length=30
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)
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translation = tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0]
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print(translation)
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```
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## License
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The model is distributed under the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)**. The full license text can be found in the accompanying `licenses_by-nc-sa_4.0_legalcode.txt` file.
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## Citation
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Please find the paper<a href="https://arxiv.org/pdf/2409.11404" target="_blank" style="margin-right: 15px; margin-left: 10px">here.</a>
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```
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@article{mousi2024aradicebenchmarksdialectalcultural,
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title={{AraDiCE}: Benchmarks for Dialectal and Cultural Capabilities in LLMs},
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author={Basel Mousi and Nadir Durrani and Fatema Ahmad and Md. Arid Hasan and Maram Hasanain and Tameem Kabbani and Fahim Dalvi and Shammur Absar Chowdhury and Firoj Alam},
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year={2024},
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publisher={arXiv:2409.11404},
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url={https://arxiv.org/abs/2409.11404},
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}
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```
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