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We still have public libraries that aim to serve their communities.
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But what about a model that makes a dumb ‘LLM-mistake’ and outputs 430245 when the answer is 4302459, and has clearly done most of the work? I wrote a custom partial-credit scoring function that pads shorter answers and penalises proportionally:
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