Update README.md

README.md

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----
-license: apache-2.0
-language:
-- en
-library_name: gguf
-pipeline_tag: text-generation
-tags:
-- mathematical-reasoning
-- qwen3
-- gguf
-- quantized
-- math
-- reasoning
-- fine-tuned
-base_model: PinkPixel/Crystal-Think-V2
-quantized_by: PinkPixel
----
-
-<div align="center">
-  <img src="crystal-think-v2-logo.png" alt="Crystal Think V2 Logo" width="300"/>
-</div>
-
-# 🧠 Crystal Think V2 - GGUF Quantized ✨
-
-**Optimized GGUF Quantizations for Efficient Mathematical Reasoning**
-
-> **🔗 Original Model:** [PinkPixel/Crystal-Think-V2](https://huggingface.co/PinkPixel/Crystal-Think-V2)  
-> **📦 Quantized by:** Pink Pixel  
-> **🏷️ License:** Apache 2.0  
-
----
-
-## 📋 About This Repository
-
-This repository contains **GGUF quantized versions** of Crystal Think V2, an advanced mathematical reasoning model based on Qwen3-4B. These quantized versions are optimized for **efficient inference** while maintaining excellent mathematical reasoning capabilities.
-
-### 🎯 Original Model Features
-- 🧮 **Advanced Mathematical Reasoning** with enhanced chain-of-thought
-- 📐 **Multi-step Problem Solving** with clear explanations
-- 💻 **Mathematical Code Generation** and algorithm explanation
-- 🎯 **Enhanced `<think></think>` Reasoning Format**
-- 📊 **85.2% GSM8K accuracy** (+8.8% over base Qwen3-4B)
-
----
-
-## 📦 Available Quantizations
-
-| Quantization | File Size | Use Case | Memory Required | Quality |
-|-------------|-----------|----------|-----------------|---------|
-| **Q4_K_M** | 2.3GB | Balanced efficiency | ~6GB RAM | Good |
-| **Q5_K_M** | 2.7GB | Better quality | ~7GB RAM | Very Good |
-| **Q6_K** | 3.1GB | High quality | ~8GB RAM | Excellent |
-| **Q8_0** | 4.0GB | Maximum quality | ~10GB RAM | Near-Original |
-
-### 💡 **Quantization Guide:**
-- **Q4_K_M** - Best for limited hardware, good performance
-- **Q5_K_M** - Recommended balance of speed and quality  
-- **Q6_K** - High quality with reasonable speed
-- **Q8_0** - Near-original quality, slower inference
-
----
-
-## 🚀 Quick Start
-
-### Using llama.cpp
-
-```bash
-# Download your preferred quantization
-wget https://huggingface.co/PinkPixel/Crystal-Think-V2-GGUF/resolve/main/crystal-think-v2-q5_k_m.gguf
-
-# Run with llama.cpp
-./llama.cpp/main -m crystal-think-v2-q5_k_m.gguf -p "Solve this step by step: If x + 2y = 10 and 2x - y = 5, find x and y." -n 512
-```
-
-### Using llama-cpp-python
-
-```python
-from llama_cpp import Llama
-
-# Load the model
-llm = Llama(
-    model_path="crystal-think-v2-q5_k_m.gguf",
-    n_ctx=4096,  # Context length
-    n_threads=8, # CPU threads
-    verbose=False
-)
-
-# Mathematical reasoning example
-prompt = """Solve this step by step:
-A rectangle has a length that is 3 more than twice its width. If the perimeter is 42 cm, what are the dimensions?
-
-Use <think></think> for your reasoning."""
-
-response = llm(
-    prompt,
-    max_tokens=512,
-    temperature=0.7,
-    stop=["</SOLUTION>", "<|endoftext|>"]
-)
-
-print(response["choices"][0]["text"])
-```
-
-### Using Ollama
-
-```bash
-# Create Modelfile
-echo 'FROM ./crystal-think-v2-q5_k_m.gguf' > Modelfile
-
-# Create Ollama model
-ollama create crystal-think-v2 -f Modelfile
-
-# Run the model
-ollama run crystal-think-v2 "What is the derivative of x^3 + 2x^2 - 5?"
-```
-
----
-
-## 🎯 Enhanced Reasoning Format
-
-Crystal Think V2 uses a structured reasoning approach:
-
-```
-<think>
-[Step-by-step reasoning process]
-- Variable definitions
-- Equation setup
-- Mathematical operations
-- Verification steps
-</think>
-
-<SOLUTION>
-[Final organized answer]
-1) Specific results
-2) Numerical values
-3) Units and context
-</SOLUTION>
-```
-
----
-
-## 📊 Performance Benchmarks
-
-### Original Model Performance
-| Benchmark | Score | Improvement over Base |
-|-----------|-------|----------------------|
-| **GSM8K** | 85.2% | +8.8% |
-| **MATH** | 42.1% | +10.4% |
-| **Algebra** | 78.9% | +13.7% |
-| **Geometry** | 71.3% | +12.5% |
-| **Code Math** | 82.6% | +13.5% |
-
-### GGUF Quantization Impact
-- **Q8_0**: ~99% original performance
-- **Q6_K**: ~97% original performance  
-- **Q5_K_M**: ~95% original performance
-- **Q4_K_M**: ~92% original performance
-
----
-
-## 💻 Hardware Requirements
-
-### Minimum Requirements
-| Quantization | RAM | VRAM (GPU) | CPU |
-|-------------|-----|-----------|-----|
-| Q4_K_M | 6GB | 4GB | 4 cores |
-| Q5_K_M | 7GB | 5GB | 4 cores |
-| Q6_K | 8GB | 6GB | 6 cores |
-| Q8_0 | 10GB | 8GB | 8 cores |
-
-### Recommended for Best Performance
-- **CPU**: Modern 8+ core processor
-- **RAM**: 16GB+ system memory
-- **GPU**: 8GB+ VRAM (optional, for GPU acceleration)
-
----
-
-## 🔧 Installation & Dependencies
-
-### llama.cpp
-```bash
-git clone https://github.com/ggerganov/llama.cpp
-cd llama.cpp
-make
-```
-
-### llama-cpp-python
-```bash
-pip install llama-cpp-python
-# For GPU support (optional)
-CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama-cpp-python
-```
-
-### Ollama
-```bash
-# Install Ollama
-curl -fsSL https://ollama.com/install.sh | sh
-```
-
----
-
-## 📚 Usage Examples
-
-### Basic Mathematical Problem
-```
-Input: "What is the integral of 2x + 3?"
-Expected: Step-by-step integration with explanation
-```
-
-### Complex Word Problem
-```
-Input: "A train travels 120 miles in 2 hours, then 180 miles in 3 hours. What's the average speed?"
-Expected: Detailed solution with calculations
-```
-
-### Algebraic Reasoning
-```
-Input: "Solve the system: 3x + 2y = 12, x - y = 1"
-Expected: Systematic solution using substitution or elimination
-```
-
----
-
-## 🔗 Related Links
-
-- **🏠 Original Model:** [PinkPixel/Crystal-Think-V2](https://huggingface.co/PinkPixel/Crystal-Think-V2)
-- **📖 Model Documentation:** [Crystal Think V2 README](https://huggingface.co/PinkPixel/Crystal-Think-V2/blob/main/README.md)
-- **🛠️ llama.cpp:** [GitHub Repository](https://github.com/ggerganov/llama.cpp)
-- **🐍 llama-cpp-python:** [PyPI Package](https://pypi.org/project/llama-cpp-python/)
-
----
-
-## ⚠️ Limitations
-
-- **Domain Focus**: Optimized for mathematical reasoning; may be less effective for general conversation
-- **Quantization Trade-offs**: Lower quantizations may show reduced accuracy on complex problems
-- **Language**: Primarily trained on English mathematical content
-- **Hardware Dependency**: Performance varies significantly with hardware specifications
-
----
-
-## 📈 Benchmarking Your Setup
-
-Test your quantization choice with this sample problem:
-
-```
-Prompt: "A rectangular garden has a length that is 4 meters more than twice its width. The garden is surrounded by a walkway that is 2 meters wide on all sides. If the total area (garden + walkway) is 294 square meters, find the dimensions of the garden."
-
-Expected: The model should show step-by-step reasoning and arrive at width ≈ 8.13m, length ≈ 20.26m
-```
-
----
-
-## 🤝 Contributing
-
-Found an issue with the quantizations or have suggestions for improvements? Please open an issue or reach out!
-
----
-
-## 📧 Contact & Support
-
-- **Developer:** Pink Pixel
-- **GitHub:** [https://github.com/pinkpixel-dev](https://github.com/pinkpixel-dev)
-- **Website:** [https://pinkpixel.dev](https://pinkpixel.dev)
-- **Email:** [admin@pinkpixel.dev](mailto:admin@pinkpixel.dev)
-
----
-
-## 🙏 Acknowledgments
-
-- **Original Model:** Crystal Think V2 by Pink Pixel
-- **Base Model:** [Qwen/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B) by Qwen Team
-- **Quantization Tools:** [llama.cpp](https://github.com/ggerganov/llama.cpp) by Georgi Gerganov
-- **Training Dataset:** [NVIDIA OpenMathReasoning](https://huggingface.co/datasets/nvidia/OpenMathReasoning)
-
----
-
-**Made with ❤️ by Pink Pixel** ✨  
+---
+license: apache-2.0
+language:
+- en
+library_name: gguf
+pipeline_tag: text-generation
+tags:
+- mathematical-reasoning
+- qwen3
+- gguf
+- quantized
+- math
+- reasoning
+- fine-tuned
+base_model: PinkPixel/Crystal-Think-V2
+quantized_by: PinkPixel
+---
+
+<div align="center">
+  <img src="crystal-think-v2-logo.png" alt="Crystal Think V2 Logo" width="400"/>
+</div>
+
+# 🧠 Crystal Think V2 - GGUF Quantized ✨
+
+**Optimized GGUF Quantizations for Efficient Mathematical Reasoning**
+
+> **🔗 Original Model:** [PinkPixel/Crystal-Think-V2](https://huggingface.co/PinkPixel/Crystal-Think-V2)  
+> **📦 Quantized by:** Pink Pixel  
+> **🏷️ License:** Apache 2.0  
+
+---
+
+## 📋 About This Repository
+
+This repository contains **GGUF quantized versions** of Crystal Think V2, an advanced mathematical reasoning model based on Qwen3-4B. These quantized versions are optimized for **efficient inference** while maintaining excellent mathematical reasoning capabilities.
+
+### 🎯 Original Model Features
+- 🧮 **Advanced Mathematical Reasoning** with enhanced chain-of-thought
+- 📐 **Multi-step Problem Solving** with clear explanations
+- 💻 **Mathematical Code Generation** and algorithm explanation
+- 🎯 **Enhanced `<think></think>` Reasoning Format**
+- 📊 **85.2% GSM8K accuracy** (+8.8% over base Qwen3-4B)
+
+---
+
+## 📦 Available Quantizations
+
+| Quantization | File Size | Use Case | Memory Required | Quality |
+|-------------|-----------|----------|-----------------|---------|
+| **Q4_K_M** | 2.3GB | Balanced efficiency | ~6GB RAM | Good |
+| **Q5_K_M** | 2.7GB | Better quality | ~7GB RAM | Very Good |
+| **Q6_K** | 3.1GB | High quality | ~8GB RAM | Excellent |
+| **Q8_0** | 4.0GB | Maximum quality | ~10GB RAM | Near-Original |
+
+### 💡 **Quantization Guide:**
+- **Q4_K_M** - Best for limited hardware, good performance
+- **Q5_K_M** - Recommended balance of speed and quality  
+- **Q6_K** - High quality with reasonable speed
+- **Q8_0** - Near-original quality, slower inference
+
+---
+
+## 🚀 Quick Start
+
+### Using llama.cpp
+
+```bash
+# Download your preferred quantization
+wget https://huggingface.co/PinkPixel/Crystal-Think-V2-GGUF/resolve/main/crystal-think-v2-q5_k_m.gguf
+
+# Run with llama.cpp
+./llama.cpp/main -m crystal-think-v2-q5_k_m.gguf -p "Solve this step by step: If x + 2y = 10 and 2x - y = 5, find x and y." -n 512
+```
+
+### Using llama-cpp-python
+
+```python
+from llama_cpp import Llama
+
+# Load the model
+llm = Llama(
+    model_path="crystal-think-v2-q5_k_m.gguf",
+    n_ctx=4096,  # Context length
+    n_threads=8, # CPU threads
+    verbose=False
+)
+
+# Mathematical reasoning example
+prompt = """Solve this step by step:
+A rectangle has a length that is 3 more than twice its width. If the perimeter is 42 cm, what are the dimensions?
+
+Use <think></think> for your reasoning."""
+
+response = llm(
+    prompt,
+    max_tokens=512,
+    temperature=0.7,
+    stop=["</SOLUTION>", "<|endoftext|>"]
+)
+
+print(response["choices"][0]["text"])
+```
+
+### Using Ollama
+
+```bash
+# Create Modelfile
+echo 'FROM ./crystal-think-v2-q5_k_m.gguf' > Modelfile
+
+# Create Ollama model
+ollama create crystal-think-v2 -f Modelfile
+
+# Run the model
+ollama run crystal-think-v2 "What is the derivative of x^3 + 2x^2 - 5?"
+```
+
+---
+
+## 🎯 Enhanced Reasoning Format
+
+Crystal Think V2 uses a structured reasoning approach:
+
+```
+<think>
+[Step-by-step reasoning process]
+- Variable definitions
+- Equation setup
+- Mathematical operations
+- Verification steps
+</think>
+
+<SOLUTION>
+[Final organized answer]
+1) Specific results
+2) Numerical values
+3) Units and context
+</SOLUTION>
+```
+
+---
+
+## 📊 Performance Benchmarks
+
+### Original Model Performance
+| Benchmark | Score | Improvement over Base |
+|-----------|-------|----------------------|
+| **GSM8K** | 85.2% | +8.8% |
+| **MATH** | 42.1% | +10.4% |
+| **Algebra** | 78.9% | +13.7% |
+| **Geometry** | 71.3% | +12.5% |
+| **Code Math** | 82.6% | +13.5% |
+
+### GGUF Quantization Impact
+- **Q8_0**: ~99% original performance
+- **Q6_K**: ~97% original performance  
+- **Q5_K_M**: ~95% original performance
+- **Q4_K_M**: ~92% original performance
+
+---
+
+## 💻 Hardware Requirements
+
+### Minimum Requirements
+| Quantization | RAM | VRAM (GPU) | CPU |
+|-------------|-----|-----------|-----|
+| Q4_K_M | 6GB | 4GB | 4 cores |
+| Q5_K_M | 7GB | 5GB | 4 cores |
+| Q6_K | 8GB | 6GB | 6 cores |
+| Q8_0 | 10GB | 8GB | 8 cores |
+
+### Recommended for Best Performance
+- **CPU**: Modern 8+ core processor
+- **RAM**: 16GB+ system memory
+- **GPU**: 8GB+ VRAM (optional, for GPU acceleration)
+
+---
+
+## 🔧 Installation & Dependencies
+
+### llama.cpp
+```bash
+git clone https://github.com/ggerganov/llama.cpp
+cd llama.cpp
+make
+```
+
+### llama-cpp-python
+```bash
+pip install llama-cpp-python
+# For GPU support (optional)
+CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama-cpp-python
+```
+
+### Ollama
+```bash
+# Install Ollama
+curl -fsSL https://ollama.com/install.sh | sh
+```
+
+---
+
+## 📚 Usage Examples
+
+### Basic Mathematical Problem
+```
+Input: "What is the integral of 2x + 3?"
+Expected: Step-by-step integration with explanation
+```
+
+### Complex Word Problem
+```
+Input: "A train travels 120 miles in 2 hours, then 180 miles in 3 hours. What's the average speed?"
+Expected: Detailed solution with calculations
+```
+
+### Algebraic Reasoning
+```
+Input: "Solve the system: 3x + 2y = 12, x - y = 1"
+Expected: Systematic solution using substitution or elimination
+```
+
+---
+
+## 🔗 Related Links
+
+- **🏠 Original Model:** [PinkPixel/Crystal-Think-V2](https://huggingface.co/PinkPixel/Crystal-Think-V2)
+- **📖 Model Documentation:** [Crystal Think V2 README](https://huggingface.co/PinkPixel/Crystal-Think-V2/blob/main/README.md)
+- **🛠️ llama.cpp:** [GitHub Repository](https://github.com/ggerganov/llama.cpp)
+- **🐍 llama-cpp-python:** [PyPI Package](https://pypi.org/project/llama-cpp-python/)
+
+---
+
+## ⚠️ Limitations
+
+- **Domain Focus**: Optimized for mathematical reasoning; may be less effective for general conversation
+- **Quantization Trade-offs**: Lower quantizations may show reduced accuracy on complex problems
+- **Language**: Primarily trained on English mathematical content
+- **Hardware Dependency**: Performance varies significantly with hardware specifications
+
+---
+
+## 📈 Benchmarking Your Setup
+
+Test your quantization choice with this sample problem:
+
+```
+Prompt: "A rectangular garden has a length that is 4 meters more than twice its width. The garden is surrounded by a walkway that is 2 meters wide on all sides. If the total area (garden + walkway) is 294 square meters, find the dimensions of the garden."
+
+Expected: The model should show step-by-step reasoning and arrive at width ≈ 8.13m, length ≈ 20.26m
+```
+
+---
+
+## 🤝 Contributing
+
+Found an issue with the quantizations or have suggestions for improvements? Please open an issue or reach out!
+
+---
+
+## 📧 Contact & Support
+
+- **Developer:** Pink Pixel
+- **GitHub:** [https://github.com/pinkpixel-dev](https://github.com/pinkpixel-dev)
+- **Website:** [https://pinkpixel.dev](https://pinkpixel.dev)
+- **Email:** [admin@pinkpixel.dev](mailto:admin@pinkpixel.dev)
+
+---
+
+## 🙏 Acknowledgments
+
+- **Original Model:** Crystal Think V2 by Pink Pixel
+- **Base Model:** [Qwen/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B) by Qwen Team
+- **Quantization Tools:** [llama.cpp](https://github.com/ggerganov/llama.cpp) by Georgi Gerganov
+- **Training Dataset:** [NVIDIA OpenMathReasoning](https://huggingface.co/datasets/nvidia/OpenMathReasoning)
+
+---
+
+**Made with ❤️ by Pink Pixel** ✨  
 *"Dream it, Pixel it"*