Update README.md

README.md

@@ -33,6 +33,26 @@ tags:
 - lightweight
 - mobile-nlp
 - ner
+- on-device-nlp
+- privacy-first
+- cpu-inference
+- speech-intent
+- offline-nlp
+- tiny-bert
+- bert-variant
+- efficient-nlp
+- edge-ml
+- tiny-ml
+- aiot
+- embedded-nlp
+- low-latency
+- smart-devices
+- edge-inference
+- ml-on-microcontrollers
+- android-nlp
+- offline-chatbot
+- esp32-nlp
+- tflite-compatible
 metrics:
 - accuracy
 - f1
@@ -43,7 +63,7 @@ library_name: transformers
 
 ![Banner](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiXuCVtFRol6PCwE1ndpw4TE8C_tbbRYPBkzCnriupCjUG9UsYoviXpe43Ud-hkX-G6dDk1EYaTdEkTz38BgmMvprAYzSK8MIZ8CaCVY7m7gAu_ghWYjxKJPzS53LLiuNv7O5uG23ou1Ot137ORyz9bFA8KIKQHoj0BojJ8nHeItuHXD68SlisTZuQ2z8E/s16000/bert-%20lite.jpg)
 
-# 🧠 BERT-Lite — Ultra-Lightweight BERT for Edge & IoT Efficiency 🚀
+# 🧠 BERT-Lite : Ultra-Lightweight BERT for Edge & IoT Efficiency 🚀
 
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 [![Model Size](https://img.shields.io/badge/Size-~10MB-blue)](#)
@@ -72,7 +92,11 @@ library_name: transformers
 
 ## Overview
 
-`BERT-Lite` is an **ultra-lightweight** NLP model derived from **google/bert_uncased_L-2_H-64_A-2**, optimized for **real-time inference** on **edge and IoT devices**. With a quantized size of **~10MB** and **~2M parameters**, it delivers efficient contextual language understanding for highly resource-constrained environments like microcontrollers, wearables, and smart home devices. Designed for **low-latency** and **offline operation**, BERT-Lite is perfect for privacy-first applications requiring intent detection, text classification, or semantic understanding with minimal connectivity.
+**BERT-Lite** is an **ultra-lightweight**, general-purpose NLP model derived from [google/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased), designed for **real-time inference** in highly constrained environments such as **edge devices, microcontrollers, and smart home systems**.
+
+With a quantized size of just **~10MB** and **~2M parameters**, BERT-Lite enables efficient **contextual language understanding** for both **general NLP tasks** and **resource-sensitive applications**.
+
+Whether you're building a privacy-first mobile app, an offline assistant, or a smart IoT device, BERT-Lite offers fast, accurate NLP performance without relying on cloud services.
 
 - **Model Name**: BERT-Lite
 - **Size**: ~10MB (quantized)