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In large language models like ChatGPT, once the input has been processed and the model produces a final hidden vector - essentially a compact summary of everything seen so far - that vector must be converted back into actual words. This is done using an unembedding matrix, which maps the hidden vector back into the model’s vocabulary space. This unembedding matrix is effectively the transpose of the embedding matrix used at the start. It transforms the hidden vector into a set of raw scores, one
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Wait, AI doesn’t actually read words? 🤯 Instead of reading a dictionary, Large Language Models like ChatGPT use something called 'Tokens.' Think of them as a hyper-efficient abstraction of human language that lets AI process entire books in seconds! Here's exactly how it works👇 Don't forget to save this if you're learning about AI! #aitokens #chatgpt #machinelearning #artificialintelligence #techreels #codinglife #techeducation #llm #gemini #programming | KodeKloud
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