Update README.md

README.md

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 ## Overview
 
-`NeuroBERT` is an **advanced lightweight** NLP model derived from **google/bert-base-uncased**, optimized for **real-time inference** on **resource-constrained devices**. With a quantized size of **~57MB** and **~30M parameters**, it delivers powerful contextual language understanding for real-world applications in environments like mobile apps, wearables, microcontrollers, and smart home devices. Designed for **low-latency**, **offline operation**, and **real-world intelligence**, it’s ideal for privacy-first applications requiring robust intent detection, classification, and semantic understanding with limited connectivity.
+`NeuroBERT` is an **advanced lightweight** NLP model derived from **google/bert-base-uncased**, built specifically for **real-time inference** on **resource-constrained environments** such as edge devices, embedded systems, and mobile platforms. With a **quantized footprint of ~57MB** and approximately **30 million parameters**, it strikes a powerful balance between model performance and deployment efficiency.
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+Designed for **low-latency**, **offline-first**, and **privacy-preserving** applications, `NeuroBERT` delivers efficient **contextual language understanding** - making it suitable not only for IoT tasks but also for **general-purpose NLP**, including:
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+- **Intent detection**
+- **Text classification**
+- **Semantic similarity**
+- **Entity recognition**
+- **Voice command parsing**
+- **Smart search enhancement**
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+Thanks to its compact size and optimized architecture, `NeuroBERT` is well-suited for running directly on devices like **smartphones**, **wearables**, **microcontrollers (e.g., Raspberry Pi, ESP32)**, and **smart appliances**, without requiring constant cloud connectivity.
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+Whether you're building a **privacy-first mobile app**, a **voice-activated smart assistant**, or a **real-time embedded NLP solution**, `NeuroBERT` enables fast, reliable language processing with minimal overhead and high adaptability across domains such as **consumer tech**, **automotive AI**, **home automation**, **healthcare**, and **enterprise NLP**.
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 - **Model Name**: NeuroBERT
 - **Size**: ~57MB (quantized)