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README.md

@@ -57,7 +57,7 @@ model-index:
 
 **A high-performance Named Entity Recognition model with superior accuracy and structured JSON output.**
 
-[![Model Size](https://img.shields.io/badge/Model_Size-143MB-blue)](https://huggingface.co/)
+[![Model Size](https://img.shields.io/badge/Model_Size-369MB-blue)](https://huggingface.co/)
 [![Architecture](https://img.shields.io/badge/Architecture-LlamaForCausalLM-green)](https://huggingface.co/)
 [![Context Window](https://img.shields.io/badge/Context-2048_Tokens-orange)](https://huggingface.co/)
 [![License](https://img.shields.io/badge/License-Apache_2.0-yellow)](https://www.apache.org/licenses/LICENSE-2.0)
@@ -75,7 +75,7 @@ model-index:
 ### Key Features
 - 🎯 **Excellent NER Performance**: 95.1% F1 score on entity recognition tasks
 - 📊 **Entity Classification**: Accurately categorizes PERSON, ORG, LOC, and MISC entities
-- 📏 **Optimized Size**: 143MB (Q8_0 quantized)
+- 📏 **Optimized Size**: 369MB (Q8_0 quantized)
 - ⚡ **Efficient Inference**: 323.3ms average response time
 - 🔄 **Local Processing**: No data sent to external servers
 - 🏗️ **Structured JSON Output**: Clean, parseable entity extraction results
@@ -269,7 +269,7 @@ John Smith works at Google in New York and uses Python programming language.
 - **Context Window**: 2,048 tokens
 - **Max Position Embeddings**: 2,048
 - **Quantization**: GGUF (Q8_0 quantization)
-- **File Size**: 143MB
+- **File Size**: 369MB
 - **Memory Requirements**: 8GB RAM minimum, 16GB recommended
 
 ### Training Details