<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>FP8 on Negi AI Lab</title><link>https://ai.negi-lab.com/tags/fp8/</link><description>Recent content in FP8 on Negi AI Lab</description><image><title>Negi AI Lab</title><url>https://ai.negi-lab.com/images/og-default.png</url><link>https://ai.negi-lab.com/images/og-default.png</link></image><generator>Hugo -- 0.154.5</generator><language>ja</language><lastBuildDate>Fri, 25 Sep 2026 20:26:38 +0900</lastBuildDate><atom:link href="https://ai.negi-lab.com/tags/fp8/index.xml" rel="self" type="application/rss+xml"/><item><title>NVIDIA/Model-Optimizer 使い方と推論コストを最小化する最適化手法の導入</title><link>https://ai.negi-lab.com/posts/nvidia-model-optimizer-review-quantization/</link><pubDate>Fri, 25 Sep 2026 00:00:00 +0900</pubDate><guid>https://ai.negi-lab.com/posts/nvidia-model-optimizer-review-quantization/</guid><description>量子化、蒸留、枝刈りなどバラバラだった最適化手法をNVIDIA公式が1つのライブラリに統合した。。TensorRT-LLMやvLLMへのデプロイを前提とし...</description></item></channel></rss>