Update README.md

README.md

@@ -20,20 +20,8 @@ base_model:
 # 🔥 InternVL3-38B-FP8-Dynamic: Optimized Vision-Language Model 🔥
 This is a **FP8 dynamic quantized** version of [OpenGVLab/InternVL3-38B](https://huggingface.co/OpenGVLab/InternVL3-38B), optimized for high-performance inference with vLLM. 
 The model utilizes **dynamic FP8 quantization** for optimal ease of use and deployment, achieving significant speedup with minimal accuracy degradation on vision-language tasks.
-## 🚀 Key Features
-- **FP8 Dynamic Quantization**
-- **Vision-Language Optimized**: Specialized quantization recipe that preserves visual understanding
-- **vLLM Ready**: Seamless integration with vLLM for production deployment  
-- **Memory Efficient**: ~50% memory reduction compared to FP16 original
-- **Performance Boost**: Significant faster inference on H100/L40S GPUs
-## 📊 Model Details
-- **Original Model**: [OpenGVLab/InternVL3-38B](https://huggingface.co/OpenGVLab/InternVL3-38B)
-- **Source Model**: OpenGVLab/InternVL3-38B
-- **Quantized Model**: InternVL3-38B-FP8-Dynamic
-- **Quantization Method**: FP8 Dynamic (W8A8) 
-- **Quantization Library**: [LLM Compressor](https://github.com/vllm-project/llm-compressor) v0.5.2.dev112+g6800f811
-- **Quantized by**: [brandonbeiler](https://huggingface.co/brandonbeiler)
-## 🔧 Usage
+
+## Just Run it!
 ### With vLLM (Recommended)
 ```python
 from vllm import LLM, SamplingParams
@@ -51,6 +39,20 @@ response = model.generate("Describe this image: <image>", sampling_params)
 print(response[0].outputs[0].text)
 ```
 
+## 🚀 Key Features
+- **FP8 Dynamic Quantization**
+- **Vision-Language Optimized**: Specialized quantization recipe that preserves visual understanding
+- **vLLM Ready**: Seamless integration with vLLM for production deployment  
+- **Memory Efficient**: ~50% memory reduction compared to FP16 original
+- **Performance Boost**: Significant faster inference on H100/L40S GPUs
+## 📊 Model Details
+- **Original Model**: [OpenGVLab/InternVL3-38B](https://huggingface.co/OpenGVLab/InternVL3-38B)
+- **Source Model**: OpenGVLab/InternVL3-38B
+- **Quantized Model**: InternVL3-38B-FP8-Dynamic
+- **Quantization Method**: FP8 Dynamic (W8A8) 
+- **Quantization Library**: [LLM Compressor](https://github.com/vllm-project/llm-compressor) v0.5.2.dev112+g6800f811
+- **Quantized by**: [brandonbeiler](https://huggingface.co/brandonbeiler)
+
 ## 🏗️ Technical Specifications
 ### Hardware Requirements
 - **Inference**: 47GB VRAM (+ Context)