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README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-0.6B
+tags:
+- quantization
+- neural-compressor
+- qat
+- quantization-aware-training
+- qwen3
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# Qwen3-0.6B Quantized with QAT
+
+This model is a quantized version of `Qwen/Qwen3-0.6B` using **Quantization Aware Training (QAT)** with Intel Neural Compressor.
+
+## 🚀 Model Details
+
+- **Base Model**: Qwen/Qwen3-0.6B  
+- **Quantization Method**: Quantization Aware Training (QAT)
+- **Framework**: Intel Neural Compressor
+- **Model Size**: Significantly reduced from original
+- **Performance**: Maintains quality while improving efficiency
+
+## 📊 Benefits
+
+✅ **Smaller model size** - Reduced storage requirements  
+✅ **Faster inference** - Optimized for deployment  
+✅ **Lower memory usage** - More efficient resource utilization  
+✅ **Maintained quality** - QAT preserves model performance  
+
+## 💻 Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the quantized model
+model = AutoModelForCausalLM.from_pretrained("Thomaschtl/qwen3-0.6b-qat-test")
+tokenizer = AutoTokenizer.from_pretrained("Thomaschtl/qwen3-0.6b-qat-test")
+
+# Generate text
+prompt = "The future of AI is"
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=100, do_sample=True, temperature=0.7)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## ⚙️ Quantization Details
+
+- **Training Method**: Quantization Aware Training
+- **Optimizer**: AdamW
+- **Learning Rate**: 5e-5  
+- **Batch Size**: 2
+- **Epochs**: 1 (demo configuration)
+
+## 🔧 Technical Info
+
+This model was quantized using Intel Neural Compressor's QAT approach, which:
+1. Simulates quantization during training
+2. Allows model weights to adapt to quantization
+3. Maintains better accuracy than post-training quantization
+
+## 📝 Citation
+
+If you use this model, please cite:
+
+```
+@misc{qwen3-qat,
+  title={Qwen3-0.6B Quantized with QAT},
+  author={Thomaschtl},
+  year={2025},
+  publisher={Hugging Face},
+  url={https://huggingface.co/Thomaschtl/qwen3-0.6b-qat-test}
+}
+```
+
+## ⚖️ License
+
+This model follows the same license as the base model (Apache 2.0).