{"repo":"stas00/ml-engineering","free":true,"listed":false,"github":"https://github.com/stas00/ml-engineering","clone":"git clone https://github.com/stas00/ml-engineering.git","description":"Machine Learning Engineering Open Book","language":"Python","stars":18646,"topics":["pytorch","slurm","large-language-models","llm","machine-learning","scalability","transformers","machine-learning-engineering","mlops","ai"],"license":"CC-BY-SA-4.0","category":"machine-learning","readme_excerpt":"Machine Learning Engineering Open Book This is an open collection of methodologies, tools and step by step instructions to help with successful training and fine-tuning of large language models and multi-modal models and their inference. This is a technical material suitable for LLM/VLM training engineers and operators. That is the content here contains lots of scripts and copy-n-paste commands to enable you to quickly address your needs. This repo is an ongoing brain dump of my experiences training Large Language Models (LLM) (and VLMs); a lot of the know-how I acquired while training the open-source BLOOM-176B model in 2022 and IDEFICS-80B multi-modal model in 2023, and RAG models at Contextual.AI in 2024. I've been compiling this information mostly for myself so that I could quickly find solutions I have already researched in the past and which have worked, but as usual I'm happy to share these notes with the wider ML community. Table of Contents Part 1. Insights 1. The AI Battlefield Engineering - what you need to know in order to succeed. 1. How to Choose a Cloud Provider - these questions will empower you to have a successful compute cloud experience. 1. When Is It Worth Upgrading GPUs? - a practical framework for deciding whether a GPU generation upgrade is worth its cost, worked through on a real H200 → B200 benchmark. Part 2. Hardware 1. Compute - accelerators, CPUs, CPU memory. 1. Storage - local, distributed and shared file systems. 1. Network - intra- and inter-no","default_branch":null,"files":null,"tree":[],"storefront":"/r/stas00","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/stas00/ml-engineering/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}