[no ci] examples README

examples/README.md

@@ -19,6 +19,7 @@ This directory contains various example notebooks using *ktrain*.  The directory
   - [Universal Information Extraction](#extraction): an example of using a Question-Answering model for information extraction
   - [Keyphrase Extraction](#kwextraction): an example of keyphrase extraction in **ktrain**
   - [Indonesian Text Examples](#indonesian):  examples such as zero-Shot text classification and question-answering on Indonesian text by [Sandy Khosasi](https://github.com/ilos-vigil)
+  - [Generative AI Examples](#generativeai):  provide instructions to a language model running on your own machine to solve various tasks
 - `vision`:  
   - [image classification](#imageclass):  models for image datasetsimage classification examples using various models and datasets
   - [image regression](#imageregression): example of predicting numerical values purely from images/photos
@@ -154,6 +155,7 @@ The objective of the CoNLL2003 task is to classify sequences of words as belongi
 ### <a name="extraction"></a>Universal Information Extraction: [qa_information_extraction.ipynb](https://github.com/amaiya/ktrain/tree/master/examples/text)
 ### <a name="kwextraction"></a>Keyphrase Extraction: [keyword_extraction_example.ipynb](https://github.com/amaiya/ktrain/tree/master/examples/text)
 ### <a name="indonesian"></a> [Indonesian NLP examples by Sandy Khosasi](https://github.com/ilos-vigil/ktrain-assessment-study) including Indonesian question-answering, emotion recognition, and document similarity
+### <a name="generativeai"></a> Generative AI Using GPT[generative_ai_example.ipynb]((https://github.com/amaiya/ktrain/tree/master/examples/text/generative_ai_example.ipynb)
 
 
 ## Vision Data