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French Healthcare NER Model (Educational Version)

This French Healthcare NER model is part of the healthcare NLP case study featured in the book Natural Language Processing on Oracle Cloud Infrastructure: Building Transformer-Based NLP Solutions Using Oracle AI and Hugging Face. Dive into Chapter 6 for a comprehensive, step-by-step guide on building this model.

πŸ“š Purpose and Scope

This model is designed to complement Chapter 6 of the book, allowing readers to:

  • Explore the Model: Experiment with the healthcare NLP model built in the book without needing to train one from scratch.
  • Recreate the Case Study: Follow along with the step-by-step implementation detailed in Chapter 6.
  • Understand Key Concepts: Learn how to fine-tune and apply a healthcare NER model to French-language data.

This pre-built model simplifies the learning process and enables hands-on practice directly aligned with the book's content.

⚠️ Usage Restrictions

This is a demo model provided for educational purposes. It was trained on a limited dataset and is not intended for production use, clinical decision-making, or real-world medical applications.

  • Educational and research purposes only
  • Not licensed for commercial deployment
  • Not for production use
  • Not for medical decisions

πŸŽ“ Book Reference

This model is built as described in Chapter 6 of the book Natural Language Processing on Oracle Cloud Infrastructure. The book covers the entire NLP solution lifecycleβ€”including data preparation, model fine-tuning, deployment, and monitoring. Chapter 6 specifically focuses on:

  • Fine-tuning a pretrained model from Hugging Face Hub for healthcare Named Entity Recognition (NER)
  • Training the model using OCI’s Data Science service and Hugging Face Transformers libraries
  • Performance evaluation and best practices for robust and cost-effective NLP models

For more details, you can explore the book and Chapter 6 on the following platforms:

Citation

If you use this model, please cite the following:

@Inbook{Assoudi2024,
author="Assoudi, Hicham",
title="Model Fine-Tuning",
bookTitle="Natural Language Processing on Oracle Cloud Infrastructure: Building Transformer-Based NLP Solutions Using Oracle AI and Hugging Face",
year="2024",
publisher="Apress",
address="Berkeley, CA",
pages="249--319",
abstract="This chapter focuses on the process of fine-tuning a pretrained model for healthcare Named Entity Recognition (NER). This chapter provides an in-depth exploration of training the healthcare NER model using OCI's Data Science platform and Hugging Face tools. It covers the fine-tuning process, performance evaluation, and best practices that contribute to creating robust and cost-effective NLP models.",
isbn="979-8-8688-1073-2",
doi="10.1007/979-8-8688-1073-2_6",
url="https://doi.org/10.1007/979-8-8688-1073-2_6"
}

πŸ“ž Connect and Contact

Stay updated on my latest models and projects:
πŸ‘‰ Follow me on Hugging Face

For inquiries or professional communication, feel free to reach out:
πŸ“§ Email: [email protected]

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