<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Attention on Noureddine RAMDI</title><link>https://ramdi.fr/tags/attention/</link><description>Recent content in Attention on Noureddine RAMDI</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 23 May 2026 20:41:27 +0000</lastBuildDate><atom:link href="https://ramdi.fr/tags/attention/index.xml" rel="self" type="application/rss+xml"/><item><title>Tracing deep learning step-by-step in Excel: a hands-on guide to ai-by-hand-excel</title><link>https://ramdi.fr/github-stars/tracing-deep-learning-step-by-step-in-excel-a-hands-on-guide-to-ai-by-hand-excel/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/tracing-deep-learning-step-by-step-in-excel-a-hands-on-guide-to-ai-by-hand-excel/</guid><description>Explore how ai-by-hand-excel implements deep learning architectures like Transformers entirely in Excel formulas, exposing the math behind AI step-by-step without code.</description></item><item><title>vLLM: Efficient large language model serving with paged attention and continuous batching</title><link>https://ramdi.fr/github-stars/vllm-efficient-large-language-model-serving-with-paged-attention-and-continuous-batching/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/vllm-efficient-large-language-model-serving-with-paged-attention-and-continuous-batching/</guid><description>vLLM is a Python library for high-throughput LLM inference using paged attention and continuous batching. It supports quantization, distributed inference, and an OpenAI-compatible API.</description></item></channel></rss>