The answer
A logit is an unnormalized model score. Softmax converts a collection of logits into nonnegative probabilities that sum to one across the available vocabulary.
How does an LLM assign probabilities to possible next tokens?
How does softmax turn vocabulary logits into probabilities?
More FAQs in How does an LLM assign probabilities to possible next tokens?
No. Each selected token changes the sequence used for the next prediction. The model therefore computes a new conditional distribution as generation progresses.
Yes. Their phrasing, frequency in training patterns, and compatibility with the prompt can differ. Probability under the model is not the same as correctness.
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