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EXHave you ever thought how do transformers like ChatGPT process text?💡
It all starts with tokenization, where words are broken down into smaller units called tokens – these can be full words, subwords, or even single letters, depending on the tokenizer used.
🔢 Next step: Each token is converted into a vector (a list of numbers) via an embedding layer. These vectors exist in high-dimensional space with hundreds or thousands of dimensions, positioning tokens with similar meanings closer together.
🤝 Why? This helps the model understand the relationships between words.
Finally, these vectors go through the transformer’s attention layers, allowing the model to analyse how words connect and influence each other to generate the coherent, meaningful responses we see.
📸 Credit: @3blue1brown
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