LLMs-from-scratch open source analysis

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Project overview

⭐ 80199 · Jupyter Notebook · Last activity on GitHub: 2025-11-25

GitHub: https://github.com/rasbt/LLMs-from-scratch

Why it matters for engineering teams

LLMs-from-scratch addresses the need for engineering teams to understand and build large language models from the ground up using PyTorch. It is particularly valuable for machine learning and AI engineering roles seeking a clear, step-by-step implementation to deepen their practical knowledge of generative AI and transformer architectures. While the project is educational and well-structured, it is not a production ready solution for deployment in live environments due to its focus on clarity over optimisation and scalability. Teams looking for a self hosted option for large-scale language models should consider more mature frameworks. This open source tool for engineering teams is best suited for learning, prototyping, and research rather than immediate production use, highlighting the trade off between transparency and operational robustness.

When to use this project

LLMs-from-scratch is a strong choice when teams need to build foundational understanding or prototype custom language models with full control over the code. For production deployments requiring high performance and scalability, teams should consider established libraries and services that offer optimised, battle-tested implementations.

Team fit and typical use cases

Machine learning engineers and AI researchers benefit most from this repository as it provides a hands-on approach to implementing language models. They typically use it for experimentation, teaching, and developing proof-of-concept chatbots or generative AI features. This project often appears in internal tooling, research projects, and early-stage product development where understanding model mechanics is critical.

Best suited for

Topics and ecosystem

ai artificial-intelligence chatbot chatgpt deep-learning from-scratch generative-ai gpt language-model large-language-models llm machine-learning neural-networks python pytorch transformers

Activity and freshness

Latest commit on GitHub: 2025-11-25. Activity data is based on repeated RepoPi snapshots of the GitHub repository. It gives a quick, factual view of how alive the project is.