This repository walks through implementing a ChatGPT like language model in PyTorch, step by step.
ML Engineering
This open book collects methods, tools, and instructions for training, fine-tuning, and running machine learning models.
About ML Engineering
ML Engineering is an open book on GitHub by Stas Bekman that collects methods, tools, and step-by-step instructions for training, fine-tuning, and running large language models and multi-modal models. The author describes it as an ongoing collection of notes from training projects including BLOOM-176B, IDEFICS-80B, and RAG models. The material is organized into parts covering insights, hardware, orchestration, training, inference, development, and miscellaneous resources.
The content is technical and includes many scripts and copy-and-paste commands. It is written for LLM and VLM training engineers and operators. Ebook versions in PDF and EPUB are available, but the author rebuilds them only occasionally, so the latest content may appear only in the repository or in build instructions provided by the author.
Key features
- Guides on accelerators, CPUs, memory, storage, and intra- and inter-node networking
- Orchestration guides covering container and resource management and SLURM
- Training and fine-tuning guides for large language and multi-modal models
- Debugging and troubleshooting guides, plus testing tips and tools
- Key comparison tables for accelerator TFLOPS, memory, and network speeds
- Two SKILL.md files for teaching AI agents about ML training and GPU cluster evaluation
Best for: ML engineers and operators who train, fine-tune, or run large language and multi-modal models and need technical reference commands and scripts.
Good for
- Contains scripts and copy-and-paste commands for common tasks
- Covers hardware, orchestration, training, inference, and debugging in one collection
- Includes a worked example of deciding whether a GPU upgrade is worth its cost, using an H200 to B200 benchmark
Watch out for
- Written as technical material for LLM and VLM training engineers and operators
- Described as an ongoing collection, so content may change over time
- Ebook versions are rebuilt only occasionally and may not match the latest repository content
ML Engineering at a glance
- Category
- Education & Learning › Learn to Code
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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ML Engineering FAQ
What ebook formats are available?
The author provides PDF and EPUB versions. The author says the ebooks are rebuilt roughly every few weeks, and build instructions are linked for the latest versions.
Where are significant updates announced?
The author says significant updates are announced on the Twitter channel @StasBekman.
Can readers discuss topics in the repository?
Yes. The repository has community discussions where users can share experiences or start new discussions about ML engineering.
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