LocaleNLP/English_darija

Model Card for Model ID

Developed by: LocaleNLP Funded by: Internal R&D and NLP Research Grants Shared by: LocaleNLP Model type: Sequence-to-sequence Transformer model Languages Supported: English, Moroccan Darija License: Apache 2.0 Finetuned from model: mT5

Model Details

Model Description

The LocaleNLP English-Darija Model is a transformer-based translation model designed to bridge the language gap between English and Moroccan Darija (a dialect of Arabic spoken in Morocco). It is fine-tuned from mT5 to support text and text translation tasks, improving accessibility for Darija speakers in digital applications.

• Developed by: [LocaleNLP]
• Funded by [Internal R&D]: [Internal R&D and NLP Research Grants]
• Shared by [LocaleNLP]: [More Information Needed]
• Model type: [Sequence-to-sequence Transformer model]
• Language(s) (NLP): [English, Moroccan Darija]
• License: [Apache 2.0]
• Finetuned from model [mT5]: [More Information Needed]

Model Sources [optional]

• Repository: [https://huggingface.co/LocaleNLP/English_darija]
• Paper [Coming soon]: [More Information Needed]
• Demo [Try it on LocaleNLP API]: [https://localenlp.com/]

Uses

Direct Use

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Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

from transformers import pipeline

translator = pipeline("translation", model="LocaleNLP/English_darija")
text = "Hello, how are you?"
result = translator(text)
print(result)

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

• Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

• Hardware Type: [More Information Needed]
• Hours used: [More Information Needed]
• Cloud Provider: [More Information Needed]
• Compute Region: [More Information Needed]
• Carbon Emitted: [More Information Needed]

Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

BibTeX:

@misc{LocaleNLP2024EnglishDarija,
  title={LocaleNLP English-Darija Translation Model},
  author={LocaleNLP AI Research Team},
  year={2024},
  url={https://huggingface.co/LocaleNLP/English_darija}
}

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APA:

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Glossary [optional]

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Contact & Support For questions or contributions: 📧 Email: [email protected] 🌍 Website: https://www.localenlp.com GitHub: https://github.com/LocaleNLP

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Model Card Authors [optional]

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Model Card Contact

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