Build A Large Language Model CN | Awesome Repository

This project is a generative AI educational resource and natural language processing course. It serves as a technical implementation guide for building, pre-training, and fine-tuning a large language model from scratch using PyTorch.

The curriculum provides a step-by-step tutorial on large language model development, focusing specifically on the design of transformer-based text generation models. It includes dedicated instruction on parameter-efficient fine-tuning to optimize training by updating only a small subset of model weights.

The material covers the end-to-end generative AI training pipeline, including the implementation of attention mechanisms and instruction tuning workflows. It details the process of adapting pre-trained models to follow specific user instructions or perform specialized text classification tasks.

Features

Model Building Tutorials - Provides a comprehensive guide to designing and training a generative text model from scratch.
Generative AI Training - Serves as an educational resource for building and optimizing deep learning models for human-like text generation.
Instruction Tuning - Implements workflows to adapt pre-trained models to follow specific user instructions.
Model Fine-Tuning - Teaches how to adapt pre-trained models for specific tasks such as text classification and instruction following.

Features

Model Building Tutorials - Provides a comprehensive guide to designing and training a generative text model from scratch.
Generative AI Training - Serves as an educational resource for building and optimizing deep learning models for human-like text generation.
Instruction Tuning - Implements workflows to adapt pre-trained models to follow specific user instructions.
Model Fine-Tuning - Teaches how to adapt pre-trained models for specific tasks such as text classification and instruction following.