vectara
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hallucination_evaluation_model

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microsoft/deberta-v3-base

Inference Endpoints

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minseokbae commited on Feb 7

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 # Introduction
 The HHEM model is an open source model, created by [Vectara](https://vectara.com), for detecting hallucinations in LLMs. It is particularly useful in the context of building retrieval-augmented-generation (RAG) applications where a set of facts is summarized by an LLM, but the model can also be used in other contexts.
-If you are interested to learn more about RAG or experiment with Vectara, you can [sign up](https://console.vectara.com/signup) for a free Vectara account.
 Now let's dive into the details of the model.
 ## Cross-Encoder for Hallucination Detection

 # Introduction
 The HHEM model is an open source model, created by [Vectara](https://vectara.com), for detecting hallucinations in LLMs. It is particularly useful in the context of building retrieval-augmented-generation (RAG) applications where a set of facts is summarized by an LLM, but the model can also be used in other contexts.
+If you are interested to learn more about RAG or experiment with Vectara, you can [sign up](https://console.vectara.com/signup/?utm_source=huggingface&utm_medium=space&utm_term=hhem-model&utm_content=console&utm_campaign=) for a free Vectara account.
 Now let's dive into the details of the model.
 ## Cross-Encoder for Hallucination Detection