Update readme info

README.md

@@ -15,9 +15,10 @@ short_description: TextTiling using LLM Embeddings for Text Segmentation
 
 This directory contains the **demo code** for an Extended TextTiling application, which segments text into coherent chunks by leveraging **LLM embeddings** (via Sentence Transformers) and a semantic shift probability threshold.
 
-## Live Demo on Hugging Face Spaces
+## Live Demo and Code
 
 You can try out the [**LLM TextTiling Demo**](https://huggingface.co/spaces/saeedabc/llm-text-tiling-demo) in your browser—no setup required.
+Refer to a related [Github repository](https://github.com/saeedabc/llm-text-tiling) for extended functionalities such as hyper-parameter tuning with more embedding models and datasets.
 
 ## Overview
 

app.py

@@ -155,7 +155,7 @@ with gr.Blocks() as app:
     gr.Markdown("""
 # LLM TextTiling Demo
 
-An **extended** approach to text segmentation that combines **TextTiling** with **LLM embeddings**. Simply provide your text, choose an embedding model, and adjust segmentation parameters (window size, pooling, threshold). The demo will split your text into coherent segments based on **semantic shifts**.
+An **extended** approach to text segmentation that combines **TextTiling** with **LLM embeddings**. Simply provide your text, choose an embedding model, and adjust segmentation parameters (window size, pooling, threshold). The demo will split your text into coherent segments based on **semantic shifts**. Refer to the [README](https://huggingface.co/spaces/saeedabc/llm-text-tiling-demo/blob/main/README.md) for more details.
 """)
 
     with gr.Row():