rasbt/LLM-workshop-2024 resource

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1113 stars · 384 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A 4-hour hands-on coding workshop by Sebastian Raschka that teaches how large language models are implemented and used, based on his 'Build a Large Language Model From Scratch' book. It walks through coding a GPT-like LLM in PyTorch, including the data pipeline, architecture, pretraining, and finetuning with open-source libraries like LitGPT.

Use cases

• learn how LLMs work by coding one from scratch
• implement a GPT-like model in PyTorch
• understand LLM pretraining and finetuning
• hands-on workshop material for teaching LLM internals
• practice building text tokenization and data pipelines for LLMs
• load pretrained weights and finetune open-source LLMs

When to choose

• you want a guided, code-first introduction to LLM internals
• you prefer learning by implementing rather than using high-level APIs
• you need structured workshop or course material on pretraining and finetuning
• you want to complement the 'Build an LLM from Scratch' book with runnable notebooks

When to avoid

• you need a production-ready LLM training framework rather than educational code
• you want to deploy or serve LLMs in applications
• you are looking for a maintained library with API stability guarantees
• you need state-of-the-art training efficiency or distributed training at scale

Facets

learning-resource · maturity active

machine-learning llm-training deep-learning large-language-models deep-learning tutorials education python llm pytorch workshop gpt finetuning pretraining jupyter-notebooks educational gpu

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