Gemma4 Tool Calling Fixes in llama.cpp, RTX cuBLAS MatMul Bug, & Local Ollama + Whisper UI

1. 1Fix tool calling issues in llama.cpp by checking function signatures and parameter passing
2. 2Resolve the RTX cuBLAS MatMul bug by updating cuBLAS libraries or modifying the MatMul implementation
3. 3Configure local Ollama and Whisper UI for testing and debugging purposes
4. 4Test the fixes using sample inputs and verify the performance improvements
5. 5Apply the fixes to production code and monitor the results

Developers and engineers working on AI and ML projects, particularly those using llama.cpp and cuBLAS, can benefit from this knowledge to optimize their code and workflows

💡 Accurate function calls and up-to-date libraries are crucial for optimal performance in AI and ML applications

🚀 Fix tool calling issues in llama.cpp and resolve RTX cuBLAS MatMul bug for better performance! 💻