Update README.md

README.md

@@ -7,7 +7,7 @@ datasets:
 - sentence-transformers/all-nli
 language:
 - en
-new_version: v1.1
+new_version: v1.3
 base_model:
 - google-bert/bert-base-uncased
 pipeline_tag: text-classification
@@ -47,7 +47,7 @@ metrics:
 library_name: transformers
 ---
 
-![Banner](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjiN6PBPuhYCHIccZ928lJmHOOkZXqmQImFyNX8Iu8qrJ0f1tUOJQ5or518FYp8PS_APQqMCjzks0UxyoRkWOAYAbvFs_X8K9bSRpWmB8BzdlJYjRdkDPpqJcARjOifTljhVECYV9g6tIEjqxLhIU3WqUUAEuYD2WUKP3P863pXDvE79qv67P35p04mi00/s16000/NeuroBERT-Mini.jpg)
+![Banner](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgs6UMbtcJ-ZILgsgLUgT63wj2g6oQh4p_c1_rMSTdHz7bVTE3TsQl3eLCIiW3NYAa40HZEhniWjrImtW3tvy2WCsDjZTeovB1QUnM-UjYs5tX-e33B9jpmmDXM547V-KBLySAUtKNtiQqceMQwXFHJHLMX8DKjvPx-n9eUJTGmxIaN6-tifIe-gz4dUGk/s4000/NeuroBERT-Mini.jpg)
 
 # 🧠 boltuix/NeuroBERT-Mini — The Ultimate Lightweight NLP Powerhouse! 🚀
 
@@ -82,9 +82,9 @@ Say hello to `NeuroBERT-Mini`, the **game-changing NLP model** that brings **wor
 
 | Feature                | Description                                           |
 |------------------------|-------------------------------------------------------|
-| 🔍 **Architecture**    | Nimble BERT (4 layers, hidden size 256)              |
-| ⚙️ **Parameters**      | ~11M, quantized to a sleek ~35MB                     |
-| 💾 **Model Size**      | ~35MB—ideal for edge devices                         |
+| 🔍 **Architecture**    | Nimble BERT (8 layers, hidden size 256)              |
+| ⚙️ **Parameters**      | ~30M, quantized to a sleek ~50MB                     |
+| 💾 **Model Size**      | ~50MB—ideal for edge devices                         |
 | ⚡ **Speed**            | Ultra-fast inference (<50ms on edge devices)          |
 | 🌍 **Use Cases**       | NER, intent detection, offline chatbots, voice AI    |
 | 📚 **Datasets**        | Wikipedia, BookCorpus, MNLI, All-NLI                 |
@@ -179,7 +179,7 @@ Input: The capital of France is [MASK].
 - **MNLI (MultiNLI)**: Built for natural language inference.
 - **All-NLI**: Enhanced with extra NLI data for smarter understanding.
 
-*Fine-Tuning Brilliance*: Starting from `google-bert/bert-base-uncased` (12 layers, 768 hidden, 110M parameters), NeuroBERT-Mini was fine-tuned to a streamlined 4 layers, 256 hidden, and ~10M parameters, creating a compact yet powerful NLP solution for edge AI! 🪄
+*Fine-Tuning Brilliance*: Starting from `google-bert/bert-base-uncased` (12 layers, 768 hidden, 110M parameters), NeuroBERT-Mini was fine-tuned to a streamlined 8 layers, 256 hidden, and ~30M parameters, creating a compact yet powerful NLP solution for edge AI! 🪄
 
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