Update README.md

README.md

@@ -40,8 +40,8 @@ tags:
 - smart-replies
 - tone-analysis
 base_model:
-- boltuix/bert-lite
 - boltuix/bitBERT
+- boltuix/bert-mini
 ---
 
 ![Banner](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhgHs4EXWBZuQWWC-bfliV2jHZN7wsgn810HEf42UuUbdPgV9aLVIq7Hiv7sWr0aqsB5aTkiylPkytpOpimhp8Atuo3Q_kO5C6uZTuQf4YEWklXqE7jQiUfZlENL5AjNgvnpLxuBg628ztR4w276TEv8Vr9u7ER7wr6i6A8W14UQ8diNBrsS0zVMVYZVYk/s4000/bert-emotions.jpg)
@@ -76,7 +76,7 @@ base_model:
 
 ## Overview
 
-`BERT-Emotion` is a **lightweight** NLP model derived from **bert-lite** and **NeuroBERT-Mini**, fine-tuned for **short-text emotion detection** on **edge and IoT devices**. With a quantized size of **~20MB** and **~6M parameters**, it classifies text into **13 rich emotional categories** (e.g., Happiness, Sadness, Anger, Love) with high accuracy. Optimized for **low-latency** and **offline operation**, BERT-Emotion is ideal for privacy-first applications like chatbots, social media sentiment analysis, and mental health monitoring in resource-constrained environments such as mobile apps, wearables, and smart home devices.
+`BERT-Emotion` is a **lightweight** NLP model derived from **bert-mini** and **bert-micro**, fine-tuned for **short-text emotion detection** on **edge and IoT devices**. With a quantized size of **~20MB** and **~6M parameters**, it classifies text into **13 rich emotional categories** (e.g., Happiness, Sadness, Anger, Love) with high accuracy. Optimized for **low-latency** and **offline operation**, BERT-Emotion is ideal for privacy-first applications like chatbots, social media sentiment analysis, and mental health monitoring in resource-constrained environments such as mobile apps, wearables, and smart home devices.
 
 - **Model Name**: BERT-Emotion
 - **Size**: ~20MB (quantized)
@@ -534,7 +534,7 @@ For more details on each variant, visit the [BoltUIX Model Hub](https://huggingf
 
 ## Credits
 
-- **Base Models**: [boltuix/bert-lite](https://huggingface.co/boltuix/bert-lite), [boltuix/bitBERT]
+- **Base Models**: [boltuix/bert-mini](https://huggingface.co/boltuix/bert-mini), [boltuix/bert-mini]
 - **Optimized By**: Boltuix, fine-tuned and quantized for edge AI applications
 - **Library**: Hugging Face `transformers` team for model hosting and tools
 
@@ -546,8 +546,14 @@ For issues, questions, or contributions:
 - Join discussions on Hugging Face or contribute via pull requests
 - Check the [Transformers documentation](https://huggingface.co/docs/transformers) for guidance
 
+
+Train Your Own Emotion Detection AI in Minutes! | NeuroFeel + NeuroBERT | Hugging Face Tutorial
+- Check this :  [Video documentation](https://youtu.be/FccGKE1kV4Q) [to train own model](https://www.boltuix.com/2021/03/revolutionizing-nlp-deep-dive-into-bert.html)
+
+
+
 We welcome community feedback to enhance BERT-Emotion for IoT and edge applications!
 
 ## Contact
 
-- 📬 Email: [[email protected]](mailto:[email protected])
+- 📬 Email: [[email protected]](mailto:[email protected])