<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Fine-Tuning on Noureddine RAMDI</title><link>https://ramdi.fr/tags/fine-tuning/</link><description>Recent content in Fine-Tuning 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/fine-tuning/index.xml" rel="self" type="application/rss+xml"/><item><title>Navigating the LLM engineer handbook: a curated map for production-grade language models</title><link>https://ramdi.fr/github-stars/navigating-the-llm-engineer-handbook-a-curated-map-for-production-grade-language-models/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/navigating-the-llm-engineer-handbook-a-curated-map-for-production-grade-language-models/</guid><description>The LLM Engineer Handbook catalogs the full lifecycle of large language model engineering, from pretraining to prompt management, guiding engineers beyond demos to production-ready LLM apps.</description></item><item><title>Inside NousResearch's finetuning-subnet: continuous incentivized fine-tuning for LLMs on Bittensor</title><link>https://ramdi.fr/github-stars/inside-nousresearch-s-finetuning-subnet-continuous-incentivized-fine-tuning-for-llms-on-bittensor/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-nousresearch-s-finetuning-subnet-continuous-incentivized-fine-tuning-for-llms-on-bittensor/</guid><description>NousResearch&amp;rsquo;s finetuning-subnet enables continuous, incentivized fine-tuning of LLMs using synthetic data from a separate subnet, pioneering cross-subnet communication in Bittensor.</description></item><item><title>A hands-on course for mastering large language models: fine-tuning, quantization, and tooling</title><link>https://ramdi.fr/github-stars/a-hands-on-course-for-mastering-large-language-models-fine-tuning-quantization-and-tooling/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/a-hands-on-course-for-mastering-large-language-models-fine-tuning-quantization-and-tooling/</guid><description>Explore a comprehensive LLM course with practical notebooks on fine-tuning (QLoRA, DPO), quantization (GPTQ), and tools like AutoEval and LazyMergekit. Ideal for aspiring LLM engineers.</description></item><item><title>LlamaFactory: modular, extensible fine-tuning framework for large language models</title><link>https://ramdi.fr/github-stars/llamafactory-modular-extensible-fine-tuning-framework-for-large-language-models/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/llamafactory-modular-extensible-fine-tuning-framework-for-large-language-models/</guid><description>LlamaFactory offers a modular Python framework for fine-tuning 100+ LLMs with diverse algorithms and optimizations, including LoRA, QLoRA, and reinforcement learning.</description></item></channel></rss>