The Vectara Hallucination Evaluation Model (HHEM) is a specialized text classification model designed to detect hallucinations in LLM outputs. It helps developers and researchers evaluate the factual accuracy of generated text. The model is based on research papers and can be used through the Hugging Face Transformers library with custom code support.
In the Other AI space, Hallucination Evaluation Model takes a focused approach. Automatically identifying when large language models generate factually incorrect or fabricated information. It is built as an open-source project for developers. The project is open source (Apache-2.0). Hallucination Evaluation Model is available on the web and API.
Vectara builds and maintains Hallucination Evaluation Model, and it first shipped in 2023. The project is developed in the open on GitHub with 3.3k stars and 6 commits in the last 90 days. Among its 3 catalogued features are Hallucination Detection, Text Classification, and Custom Model Code. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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