Teknosys learning library

Quantize and try the model

Q4_K_M is a common starting point for balancing size and quality, not a universal optimum. Compare quantization levels against your hardware and tasks, and keep the high-precision file if you intend to create other variants.

./build/bin/llama-quantize my-model-f16.gguf my-model-Q4_K_M.gguf Q4_K_M
./build/bin/llama-cli -m my-model-Q4_K_M.gguf -p "Explain natural language processing."

Successful conversion does not guarantee good responses: use an appropriate chat template for instruction models and evaluate the quantized output against the original model.

Reference documentation: llama.cpp build instructions, Hugging Face to GGUF converter, and Hugging Face CLI guide. Commands and model support can change; review the documentation for the version you use.

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