Quantize Llama models with GGML and llama.cpp

Due to the massive size of Large Language Models (LLMs), quantization has become an essential technique to run them efficiently. By reducing the precision of their weights, you can save memory and speed up inference while preserving most of the model’s performance. Recently, 8-bit and 4-bit quantization unlocked the possibility of running LLMs on consumer hardware. Coupled with the release of Llama models and parameter-efficient techniques to fine-tune them (LoRA, QLoRA), this created a rich ecosystem of local LLMs that are now competing with OpenAI’s GPT-3.5 and GPT-4. Besides the naive approach covered <a href="https://medium.com/towards-data-science/introduction-to-weight-quantization-2494701b9c0c" rel="noopener">in this article</a>, there are three main quantization techniques: NF4, GPTQ, and GGML. <a href="https://huggingface.co/blog/4bit-transformers-bitsandbytes" rel="noopener ugc nofollow" target="_blank">NF4</a> is a static method used by QLoRA to load a model in 4-bit precision to perform fine-tuning. <a href="https://medium.com/towards-data-science/4-bit-quantization-with-gptq-36b0f4f02c34" rel="noopener">In a previous article</a>, we explored the GPTQ method and quantized our own model to run it on a consumer GPU. In this article, we will introduce the GGML technique, see how to quantize Llama models, and provide tips and tricks to achieve the best results. You can find the code on <a href="https://colab.research.google.com/drive/1pL8k7m04mgE5jo2NrjGi8atB0j_37aDD?usp=sharing" rel="noopener ugc nofollow" target="_blank">Google Colab</a> and <a href="https://github.com/mlabonne/llm-course" rel="noopener ugc nofollow" target="_blank">GitHub</a>. <h1>What is GGML?</h1> GGML is a C library focused on machine learning. It was created by Georgi Gerganov, which is what the initials “GG” stand for. This library not only provides foundational elements for machine learning, such as tensors, but also a unique binary format to distribute LLMs. <a href="https://towardsdatascience.com/quantize-llama-models-with-ggml-and-llama-cpp-3612dfbcc172">Learn More</a>