Update README.md

README.md

@@ -11,35 +11,65 @@ license: apache-2.0
 short_description: French Healthcare NER Demo from the Book NLP on OCI
 ---
 
-# Educational French Healthcare NER Demo
-Book companion for "Natural Language Processing on Oracle Cloud Infrastructure: Building Transformer-Based NLP Solutions Using Oracle AI and Hugging Face"
-
-## 🎯 Purpose
-This Space demonstrates the educational model built in Chapter 6 of the book. 
-It's designed to help you:
-- Understand NER concepts
-- Follow along with the book
-- Test your implementation
-- Learn healthcare NLP
-
-## 📚 Book Integration
-1. Read Chapters 4, 5 and 6
-2. Build the model step-by-step
-3. Compare with this demo
-4. Understand key concepts
-
-## 🚫 Not for Production
-This educational version is not suitable for:
-- Clinical use
-- Production systems
-- Commercial applications
-- Medical decisions
-
-## 💡 Ready for Production?
-Our commercial solutions offer:
-- Custom model training
-- Production deployment
-- Security compliance
-- Enterprise support
-
-[Contact for Commercial Solutions](https://typica.ai/)
+# French Healthcare NER Model (Educational Version)
+
+This Hugging Face Space provides a live demonstration of the model developed as part of the healthcare NLP case study featured throughout my book *[Natural Language Processing on Oracle Cloud Infrastructure: Building Transformer-Based NLP Solutions Using Oracle AI and Hugging Face](https://a.co/d/h0xL4lo).* Dive into Chapter 6 for a comprehensive, step-by-step guide on building this model.
+
+## 📚 Purpose and Scope
+
+This Hugging Face Space showcases the model built step-by-step in Chapters 4 to 7 of the book, covering everything from healthcare dataset creation to fine-tuning a transformer-based NER model. It provides a practical example of how NLP can be applied in healthcare to extract insights from French medical texts.
+
+Why Explore This Demo?  
+- **Experiment with the Model**: Interact with the healthcare NLP model from the book without the need to train one from scratch.  
+- **Discover What You Can Build**: Get a hands-on preview of the process detailed in the book, from healthcare dataset preparation to fine-tuning a pre-trained transformer-based NER model.  
+
+## ⚠️ Usage Restrictions
+
+This is a demo provided for educational purposes. The Model behind 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
+
+## 🎓 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 lifecycle—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:  
+- **Full Book on Springer**: [View Here](https://link.springer.com/book/10.1007/979-8-8688-1073-2)  
+- **Chapter 6 on Springer**: [Read Chapter 6](https://link.springer.com/chapter/10.1007/979-8-8688-1073-2_6)  
+- **Amazon**: [Learn More](https://a.co/d/3jDIQki)
+
+## Citation
+
+<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+If you use this model, please cite the following:
+
+```bibtex
+@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"
+}
+```
+
+## 📞 Connect and Contact
+
+Stay updated on my latest models and projects:  
+👉 **[Follow me on Hugging Face](https://huggingface.co/hassoudi)**  
+
+For inquiries or professional communication, feel free to reach out:  
+📧 **Email**: [[email protected]](mailto:[email protected])