A step-by-step guide to implementing a basic Large Language Model from scratch using PyTorch, covering everything from environment setup to model training and text generation.
The tutorial includes de
tailed code examples, optimization tips, and practical use cases while explaining core concepts like tokenization and transformer architecture.
Reasons to Read -- Learn:
how to implement a complete Large Language Model from scratch using PyTorch, with practical code examples and detailed explanations of each component.
essential optimization techniques for training LLMs, including the use of pre-trained embeddings, data augmentation, and mixed precision training using PyTorch's amp package.
how to build a working text generation system using transformer architecture, complete with code for tokenization, model architecture, and inference.
publisher: @priyanshu011109
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