LLMs-from-scratch and Building-LLMs-from-scratch

These are competitors offering similar educational implementations of GPT-style language models in PyTorch, where the significantly more established rasbt repository would be the primary choice for learning transformer architecture from scratch.

LLMs-from-scratch
66
Established
Maintenance 17/25
Adoption 10/25
Maturity 16/25
Community 23/25
Maintenance 6/25
Adoption 8/25
Maturity 15/25
Community 18/25
Stars: 87,892
Forks: 13,408
Downloads:
Commits (30d): 8
Language: Jupyter Notebook
License:
Stars: 51
Forks: 16
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
No Package No Dependents
No Package No Dependents

About LLMs-from-scratch

rasbt/LLMs-from-scratch

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

This project provides the practical code and guidance to build your own custom GPT-like large language model (LLM) from the ground up. You'll learn how to take raw text data, process it, and train a functional LLM that can generate text or follow instructions. This is designed for AI practitioners, machine learning engineers, and researchers who want to deeply understand and implement LLMs.

AI development natural language processing machine learning engineering deep learning research custom model training

About Building-LLMs-from-scratch

codewithdark-git/Building-LLMs-from-scratch

This repository guides you through the process of building a GPT-style Large Language Model (LLM) from scratch using PyTorch. The structure and approach are inspired by the book Build a Large Language Model (From Scratch) by Sebastian Raschka.

This project helps machine learning engineers and researchers understand and build large language models (LLMs) from the ground up. It provides a guided journey to construct a GPT-style model, taking raw text data and producing a trained language model capable of generating human-like text. The target user is someone with a background in machine learning and Python who wants to deeply grasp LLM architectures.

natural-language-processing machine-learning-engineering deep-learning-research language-model-development

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