What Actually Happens Inside an LLM (Forward Pass Explained)
Автор: Puru Kathuria
Загружено: 2026-01-16
Просмотров: 78
Описание:
In this video, we explain what actually happens inside a Large Language Model during the forward pass.
You will see how raw text is converted into tokens, embeddings, and positional information, how multi-head attention builds contextual representations, and how feed-forward networks turn those representations into next-token probabilities.
We walk through the complete data flow inside a decoder-only transformer, from input tokens to the output probability distribution, and clarify what a single forward pass means during training.
This video builds a clear mental model of LLM internals before diving into backpropagation, training, and inference in upcoming sessions.
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