A step-by-step guide to building and training a Large Language Model (LLM) using PyTorch. The model's task is to translate texts from English to Malay language. The core foundation of LLMs is the Transformer architecture, and this post provides a comprehensive explanation of how to build it from scratch.
Table of contents
A Step-by-Step guide to build and train an LLM named MalayGPT. This model’s task is to translate texts from English to Malay language.Step 1: Load datasetStep 2: Create TokenizerStep 3: Prepare Dataset and DataLoaderStep 4: Input Embedding and Positional EncodingStep 5: Multi-Head Attention BlockStep 6: Feedforward Network, Layer Normalization and AddAndNormStep 7: Encoder block and EncoderStep 8: Decoder block, Decoder and Projection LayerStep 9: Create and build a TransformerStep 10: Training and validation of our build LLM modelStep 11: Create a function to test new translation task with our built modelSort: