LLMs From Scratch
LLMs From Scratch is an open-source project that provides a step-by-step guide to implementing a ChatGPT-like Large Language Model (LLM) in PyTorch from scratch. The project is based on a book titled 'Build a Large Language Model (From Scratch)' and includes code for developing, pretraining, and finetuning a GPT-like LLM. The project uses PyTorch to implement the code from scratch without using any external LLM libraries. The code is designed to run on conventional laptops within a reasonable timeframe and does not require specialized hardware. The project also includes a companion video course and a sequel book titled 'Build A Reasoning Model (From Scratch)'. The project's goal is to help users understand how LLMs work from the inside out by coding them from the ground up. The project includes a range of topics, including working with text data, coding attention mechanisms, implementing a GPT model from scratch, pretraining on unlabeled data, finetuning for text classification, and finetuning to follow instructions. The project also includes a range of bonus materials, including setup recommendations, exercises, and additional code examples. Overall, LLMs From Scratch is a comprehensive resource for anyone looking to learn about LLMs and implement them from scratch.
- Category
- LLM
- Pricing
- Open Source
Problem solved
The problem that LLMs From Scratch solves is the lack of understanding of how Large Language Models (LLMs) work from the inside out. Many users may be familiar with using pre-trained LLMs, but may not have a deep understanding of how they are implemented. LLMs From Scratch provides a step-by-step guide to implementing a ChatGPT-like LLM in PyTorch from scratch, which helps users to gain a deeper understanding of how LLMs work and how to implement them. This can be particularly useful for researchers, developers, and students who want to learn about LLMs and implement them in their own projects.
Use cases
- Implementing a ChatGPT-like LLM in PyTorch from scratch
- Pretraining and finetuning a GPT-like LLM
- Working with text data and coding attention mechanisms
- Implementing a GPT model from scratch and pretraining on unlabeled data
- Finetuning for text classification and finetuning to follow instructions
Audience
- Developers
- ML Engineers
- Data Scientists
- Researchers
Pros
- Comprehensive guide to implementing a ChatGPT-like LLM from scratch
- Includes a range of topics and bonus materials
- Designed to run on conventional laptops without requiring specialized hardware
Cons
- May require a strong foundation in Python programming and deep neural networks
- Limited to implementing a GPT-like LLM in PyTorch
Official website: https://github.com/rasbt/LLMs-from-scratch
Canonical LambdaBase page: https://www.lambdabase.com/tools/llms-from-scratch