aastroza/structured-generation-benchmark
Structured Generation Evals
This project helps software developers understand how well Large Language Models (LLMs) can produce structured outputs like JSON or Pydantic data models. It takes various LLM setups and evaluates their ability to generate predictable, usable data formats or call functions correctly. Developers building applications that rely on consistent LLM output would use these evaluations.
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Use this if you are a developer integrating LLMs into software and need to choose the best method for ensuring structured, reliable outputs like JSON or for accurate function calling.
Not ideal if you are an end-user simply prompting an LLM for creative text or general information, as this project is focused on technical evaluation for developers.
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Jupyter Notebook
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Apache-2.0
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Last pushed
Sep 25, 2024
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