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Building a Large Language Model from Scratch: A Comprehensive Guide

2. The Transformer Block

Multi-head attention implementation
Feed-forward networks
Layer normalization & residual connections

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Building a Large Language Model

1. Data Collection

Dataset: Gathering a large and diverse dataset is crucial. This often involves scraping text from the web, books, and other sources. Popular datasets include the Common Crawl dataset, Wikipedia, and BookCorpus.

def forward(self, values, keys, query, mask): N = query.shape[0] value_len, key_len, query_len = values.shape[1], keys.shape[1], query.shape[1]