What Actually Happens Inside an LLM (Forward Pass Explained) скачать в хорошем качестве

What Actually Happens Inside an LLM (Forward Pass Explained)

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.