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Using Quantized Models with Ollama for Application Development Iván Palomares Carrascosa MachineLearningMastery.com

​Quantization is a frequently used strategy applied to production machine learning models, particularly large and complex ones, to make them lightweight by reducing the numerical precision of the model’s parameters (weights) — usually from 32-bit floating-point to lower representations like 8-bit integers. Quantization is a frequently used strategy applied to production machine learning models, particularly large and complex ones, to make them lightweight by reducing the numerical precision of the model’s parameters (weights) — usually from 32-bit floating-point to lower representations like 8-bit integers.  Read More  

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