Hugging Face explains decision models that return probabilities over fixed answers
Overview
Hugging Face explains decision models, which take a state and predefined questions and return probability distributions over the allowed answers without generating text.
The Hugging Face Blog post contrasts them with LLMs that output JSON, which it says can violate schemas and add generation overhead, and with classifiers that have fixed label heads.
The post also covers how decision models fit into Hugging Face's ecosystem for serving and training. It walks through each of these pieces, according to the post.
Written by AI from the articles below · updated Nov 10, 10:03 AM ET
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- Hugging Face BlogOfficialHugging Face explains decision models that return probabilities over predefined answers
AIHugging Face explains decision models, which take a state and predefined questions and return probability distributions over the allowed answers without generating text. The post contrasts them with LLMs that output JSON, citing schema violations and generation overhead, and with classifiers that have fixed label heads.
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