<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Llama on SoloSoft</title><link>https://www.solosoft.dev/es/tags/llama/</link><description>Recent content in Llama on SoloSoft</description><generator>Hugo</generator><language>es-es</language><lastBuildDate>Fri, 01 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.solosoft.dev/es/tags/llama/index.xml" rel="self" type="application/rss+xml"/><item><title>Ollama: Ejecuta LLMs Open-Source Localmente con Simplicidad Tipo Docker</title><link>https://www.solosoft.dev/es/post/ollama-local-llm-2026/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://www.solosoft.dev/es/post/ollama-local-llm-2026/</guid><description>&lt;p&gt;The world of large language models has evolved at breathtaking speed, but for most users, interacting with these powerful tools still involves sending data to someone else&amp;rsquo;s servers. Every prompt, every document, every conversation travels over the internet to a cloud API, processed on hardware you do not control, governed by terms of service you probably have not read. For developers, privacy-conscious users, and anyone building AI-powered applications, this architecture creates a fundamental tension: the most capable models require surrendering control of your data.&lt;/p&gt;
&lt;p&gt;Ollama emerged as a direct answer to this problem. It is an open-source project that wraps the complexity of running LLMs locally into a command-line interface so simple it feels like using Docker. Pull a model with &lt;code&gt;ollama pull llama3.2&lt;/code&gt;, run it with &lt;code&gt;ollama run llama3.2&lt;/code&gt;, and you have a fully functional language model running on your own hardware — no cloud connection, no API key, no data leaving your machine. What started as a developer tool has become the de facto standard for local LLM deployment, powering everything from personal AI assistants to enterprise edge deployments.&lt;/p&gt;</description></item></channel></rss>