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Category: quantization

  • I Made My AI Model 84% Smaller and It Got Better, Not Worse

    I Made My AI Model 84% Smaller and It Got Better, Not Worse The counterintuitive approach to AI optimization that’s changing how we deploy models The post I Made My AI Model 84% Smaller and It Got Better, Not Worse appeared first on Towards Data Science. Arjun Kaarat Go to original source

  • Boost 2-Bit LLM Accuracy with EoRA

    Boost 2-Bit LLM Accuracy with EoRA Quantization is one of the key techniques for reducing the memory footprint of large language models (LLMs). It works by converting the data type of model parameters from higher-precision formats such as 32-bit floating point (FP32) or 16-bit floating point (FP16/BF16) to lower-precision integer formats, typically INT8 or INT4.…

  • Model Compression: Make Your Machine Learning Models Lighter and Faster

    Model Compression: Make Your Machine Learning Models Lighter and Faster Introduction Whether you’re preparing for interviews or building Machine Learning systems at your job, model compression has become a must-have skill. In the era of LLMs, where models are getting larger and larger, the challenges around compressing these models to make them more efficient, smaller,…

  • 2-Bit VPTQ: 6.5x Smaller LLMs While Preserving 95% Accuracy

    2-Bit VPTQ: 6.5x Smaller LLMs While Preserving 95% Accuracy Very accurate 2-bit quantization for running 70B LLMs on a 24 GB GPU Continue reading on Towards Data Science » Benjamin Marie Go to original source