Categories: AI/ML Research

Using Quantized Models with Ollama for Application Development

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.
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Recent Posts

New fire just dropped: ComfyUI-CacheDiT ⚡

ComfyUI-CacheDiT brings 1.4-1.6x speedup to DiT (Diffusion Transformer) models through intelligent residual caching, with zero…

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A Beginner’s Reading List for Large Language Models for 2026

  The large language models (LLMs) hype wave shows no sign of fading anytime soon:…

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How Clarus Care uses Amazon Bedrock to deliver conversational contact center interactions

This post was cowritten by Rishi Srivastava and Scott Reynolds from Clarus Care. Many healthcare…

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Build intelligent employee onboarding with Gemini Enterprise

Employee onboarding is rarely a linear process. It’s a complex web of dependencies that vary…

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Epstein Files Reveal Peter Thiel’s Elaborate Dietary Restrictions

The latest batch of Jeffrey Epstein files shed light on the convicted sex offender’s ties…

21 hours ago

A tiny light trap could unlock million qubit quantum computers

A new light-based breakthrough could help quantum computers finally scale up. Stanford researchers created miniature…

21 hours ago