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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Chroma Radiance, Mid training but the most aesthetic model already imo

submitted by /u/Different_Fix_2217 [link] [comments]

14 hours ago

From human clicks to machine intent: Preparing the web for agentic AI

For three decades, the web has been designed with one audience in mind: People. Pages…

15 hours ago

Best GoPro Camera (2025): Compact, Budget, Accessories

You’re an action hero, and you need a camera to match. We guide you through…

15 hours ago

What tools would you use to make morphing videos like this?

submitted by /u/nikitagent [link] [comments]

2 days ago

Bias after Prompting: Persistent Discrimination in Large Language Models

A dangerous assumption that can be made from prior work on the bias transfer hypothesis…

2 days ago

Post-Training Generative Recommenders with Advantage-Weighted Supervised Finetuning

Author: Keertana Chidambaram, Qiuling Xu, Ko-Jen Hsiao, Moumita Bhattacharya(*The work was done when Keertana interned…

2 days ago