Automatically Quantize LLMs with AutoRound | Intel Software

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If you are looking to deploy faster and smaller language models, but you don’t want to experiment with finding the right quantization settings for your deployment requirements, AutoRound makes it easy. You just specify your model, a light amount of training data, how many bits you want to quantize to, whether you want to prioritize accuracy or speed, and it will automatically tune the weight rounding and clipping ranges. AutoRound supports CPUs, GPUs, and AI accelerators from multiple vendors. Learn how to get started with this coding LLM example.

Resources:
Learn more about AutoRound: https://huggingface.co/blog/autoround
AutoRound GitHub repo: https://github.com/intel/auto-round
Intel AI software resources: https://developer.intel.com/ai

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Automatically Quantize LLMs with AutoRound | Intel Software




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