Add Readme content

README.md

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----
-license: mit
----
+---
+license: mit
+tags:
+- llama-cpp
+- llama-cpp-python
+- gguf
+- cuda
+- windows
+- prebuilt-wheels
+- quantization
+- local-llm
+---
+
+# llama-cpp-python Pre-built Windows Wheels
+
+**Stop fighting with Visual Studio and CUDA Toolkit.** Just download and run.
+
+Pre-compiled `llama-cpp-python` wheels for Windows across CUDA versions and GPU architectures.
+
+## Quick Start
+
+1. **Find your GPU** in the compatibility list below
+2. **Download** the wheel for your GPU from [GitHub Releases](https://github.com/dougeeai/llama-cpp-python-wheels/releases)
+3. **Install**: `pip install <downloaded-wheel-file>.whl`
+4. **Run** your GGUF models immediately
+
+> **Platform Support:**  
+> ✅ Windows 10/11 64-bit (available now, biggest pain point)  
+> 🔜 Linux support coming soon  
+
+## Supported GPUs
+
+### RTX 50 Series (Blackwell - sm_100)
+RTX 5090, 5080, 5070 Ti, 5070, 5060 Ti, 5060, RTX PRO 6000 Blackwell, B100, B200, GB200
+
+### RTX 40 Series (Ada Lovelace - sm_89)
+RTX 4090, 4080, 4070 Ti, 4070, 4060 Ti, 4060, RTX 6000 Ada, RTX 5000 Ada, L40, L40S
+
+### RTX 30 Series (Ampere - sm_86)
+RTX 3090, 3090 Ti, 3080 Ti, 3080, 3070 Ti, 3070, 3060 Ti, 3060, RTX A6000, A5000, A4000
+
+### RTX 20 Series & GTX 16 Series (Turing - sm_75)
+RTX 2080 Ti, 2080 Super, 2070 Super, 2060, GTX 1660 Ti, 1660 Super, 1650, Quadro RTX 8000, Tesla T4
+
+[View full compatibility table →](https://github.com/dougeeai/llama-cpp-python-wheels#available-wheels)
+
+## Usage Example
+```python
+from llama_cpp import Llama
+
+# Load your GGUF model with GPU acceleration
+llm = Llama(
+    model_path="./models/llama-3-8b.Q4_K_M.gguf",
+    n_gpu_layers=-1,  # Offload all layers to GPU
+    n_ctx=2048        # Context window
+)
+
+# Generate text
+response = llm(
+    "Write a haiku about artificial intelligence:",
+    max_tokens=50,
+    temperature=0.7
+)
+
+print(response['choices'][0]['text'])
+```
+
+## Download Wheels
+
+➡️ **[Download from GitHub Releases](https://github.com/dougeeai/llama-cpp-python-wheels/releases)**
+
+### Available Configurations:
+- **CUDA Versions**: 11.8, 12.1, 13.0
+- **Python Versions**: 3.10, 3.11, 3.12, 3.13
+- **Architectures**: sm_75 (Turing), sm_86 (Ampere), sm_89 (Ada), sm_100 (Blackwell)
+
+## What This Solves
+
+❌ No Visual Studio required  
+❌ No CUDA Toolkit installation needed  
+❌ No compilation errors  
+❌ No "No CUDA toolset found" issues  
+✅ Works immediately with GGUF models  
+✅ Full GPU acceleration out of the box  
+
+## Installation
+
+Download the wheel matching your configuration and install:
+```bash
+# Example for RTX 4090 with Python 3.12 and CUDA 13.0
+pip install llama_cpp_python-0.3.16+cuda13.0.sm89.ada-cp312-cp312-win_amd64.whl
+```
+
+## Build Details
+
+All wheels are built with:
+- Visual Studio 2019/2022 Build Tools
+- Official NVIDIA CUDA Toolkits (11.8, 12.1, 13.0)
+- Optimized CMAKE_CUDA_ARCHITECTURES for each GPU generation
+- Built from official [llama-cpp-python](https://github.com/abetlen/llama-cpp-python) source
+
+## Contributing
+
+**Need a different configuration?**
+
+Open an [issue on GitHub](https://github.com/dougeeai/llama-cpp-python-wheels/issues) with:
+- OS (Windows/Linux/macOS)
+- Python version
+- CUDA version
+- GPU model
+
+## Resources
+
+- [GitHub Repository](https://github.com/dougeeai/llama-cpp-python-wheels)
+- [Report Issues](https://github.com/dougeeai/llama-cpp-python-wheels/issues)
+- [llama-cpp-python Documentation](https://github.com/abetlen/llama-cpp-python)
+- [llama.cpp Project](https://github.com/ggerganov/llama.cpp)
+
+## License
+
+MIT License - Free to use for any purpose
+
+Wheels are built from [llama-cpp-python](https://github.com/abetlen/llama-cpp-python) (MIT License)