Update README.md

README.md

@@ -73,7 +73,7 @@ library_name: transformers
 
 ## Overview
 
-`NeuroBERT-Tiny` is a **super lightweight** NLP model derived from **google/bert_uncased_L-2_H-128_A-2**, optimized for **real-time inference** on **edge and IoT devices**. With a quantized size of **~15MB** and **~4M parameters**, it delivers efficient contextual language understanding for resource-constrained environments like mobile apps, wearables, microcontrollers, and smart home devices. Designed for **low-latency** and **offline operation**, it’s perfect for privacy-first applications with limited connectivity.
+`NeuroBERT-Tiny` is a **super lightweight** NLP model derived from **google/bert-base-uncased**, optimized for **real-time inference** on **edge and IoT devices**. With a quantized size of **~15MB** and **~4M parameters**, it delivers efficient contextual language understanding for resource-constrained environments like mobile apps, wearables, microcontrollers, and smart home devices. Designed for **low-latency** and **offline operation**, it’s perfect for privacy-first applications with limited connectivity.
 
 - **Model Name**: NeuroBERT-Tiny
 - **Size**: ~15MB (quantized)