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Softmax Renormalization in Top-k Sampling
In top-k sampling, after the candidate pool is determined, the probability distribution over this restricted set can be calculated using the Softmax function applied to the token logits. If represents the logit for token , the rescaled probability is given by:
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Foundations of Large Language Models
Ch.5 Inference - Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Top-k Sampling Process
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A language model is generating text and has calculated the following probabilities for potential next tokens:
mat(0.45),rug(0.25),floor(0.15),table(0.10), andwindow(0.03). If the model uses a decoding strategy where it first identifies the 3 most probable tokens and then randomly samples one token from only that reduced group, which of the following statements is true?Effect of Candidate Pool Size on Text Generation
A language model is configured to generate text by first selecting a fixed number of the most probable next tokens and then sampling from only that reduced set. If the fixed number of tokens to consider is significantly decreased (e.g., from 100 to 5), what is the most likely impact on the generated text?
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Softmax Renormalization in Top-k Sampling