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  A specialized 4B parameter model fine-tuned for function calling and tool usage, optimized for local deployment with llama-cpp-python.
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- ## πŸš€ Features
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  - **4B Parameters** - Sweet spot for local deployment
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  - **Function Calling** - Fine-tuned on 60K function calling examples
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  - **Production Ready** - 0.518 training loss
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  - **262K Context** - Large context window for complex tasks
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- ## πŸ“¦ Model Details
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  - **Base Model**: Qwen3-4B-Instruct-2507
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  - **Fine-tuning**: LoRA on Salesforce xlam-function-calling-60k dataset
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  - **Architecture**: Qwen3 with specialized tool calling tokens
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  - **License**: Apache 2.0
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- ## πŸ› οΈ Installation
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  ### Quick Install
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  CMAKE_ARGS="-DLLAMA_BLAS=on -DLLAMA_BLAS_VENDOR=OpenBLAS" pip install llama-cpp-python
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  ```
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- ## πŸš€ Quick Start
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  ### Option 1: Using the Run Script
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  print(f"Tool calls: {tool_calls}")
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  ```
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- ## πŸ“š Examples
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  ### 1. Weather Tool Calling
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  └── .gitignore # Git ignore file
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  ```
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- ## 🀝 Contributing
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- 1. Fork the repository
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- 2. Create a feature branch
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- 3. Make your changes
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- 4. Add tests if applicable
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- 5. Submit a pull request
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- ## πŸ“„ License
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-
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- This project is licensed under the Apache 2.0 License - see the [LICENSE](LICENSE) file for details.
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-
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- ## πŸ™ Acknowledgments
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-
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- - **Qwen Team** - For the base Qwen3-4B-Instruct model
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- - **Salesforce** - For the xlam-function-calling-60k dataset
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- - **llama.cpp** - For the efficient inference engine
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- - **Manojb** - For quantization and optimization
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-
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- ## πŸ“ž Support
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-
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- - **Issues**: [GitHub Issues](https://github.com/yourusername/qwen3-4b-toolcall-llamacpp/issues)
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- - **Discussions**: [GitHub Discussions](https://github.com/yourusername/qwen3-4b-toolcall-llamacpp/discussions)
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-
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- ## πŸ”— Related Projects
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  - [llama-cpp-python](https://github.com/abetlen/llama-cpp-python) - Python bindings for llama.cpp
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  - [Qwen3](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) - Base model
 
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  A specialized 4B parameter model fine-tuned for function calling and tool usage, optimized for local deployment with llama-cpp-python.
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+ ## Features
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  - **4B Parameters** - Sweet spot for local deployment
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  - **Function Calling** - Fine-tuned on 60K function calling examples
 
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  - **Production Ready** - 0.518 training loss
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  - **262K Context** - Large context window for complex tasks
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+ ## Model Details
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  - **Base Model**: Qwen3-4B-Instruct-2507
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  - **Fine-tuning**: LoRA on Salesforce xlam-function-calling-60k dataset
 
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  - **Architecture**: Qwen3 with specialized tool calling tokens
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  - **License**: Apache 2.0
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+ ## Installation
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  ### Quick Install
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  CMAKE_ARGS="-DLLAMA_BLAS=on -DLLAMA_BLAS_VENDOR=OpenBLAS" pip install llama-cpp-python
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  ```
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+ ## Quick Start
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  ### Option 1: Using the Run Script
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  print(f"Tool calls: {tool_calls}")
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  ```
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+ ## Examples
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  ### 1. Weather Tool Calling
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  └── .gitignore # Git ignore file
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  ```
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+ ## License
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+ This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
 
 
 
 
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+ ## Related Projects
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - [llama-cpp-python](https://github.com/abetlen/llama-cpp-python) - Python bindings for llama.cpp
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  - [Qwen3](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) - Base model