A state-of-the-art fact-checking model developed by Bespoke Labs.
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Updated 8 weeks ago
8 weeks ago
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Readme
This is a grounded factuality checking model developed by Bespoke Labs.
The model takes as input a document (text) and a sentence and determines whether the sentence is supported by the document. In order to fact-check a multi-sentence claim, the claim should first be broken up into sentences. The document does not need to be chunked unless it exceeds 32K tokens.
Bespoke-MiniCheck is the SOTA fact-checking model despite its small size.
Usage
The prompt template is as follows:
Document: {document}
Claim: {claim}
The response will either be Yes or No.
Examples
Prompt
Document: A group of students gather in the school library to study for their upcoming final exams.
Claim: The students are preparing for an examination.
Response
Yes
Prompt
Document: A group of students gather in the school library to study for their upcoming final exams.
Claim: The students are on vacation.
Response
No
Model performance
The performance of these models is evaluated on our new collected benchmark (unseen by our models during training), LLM-AggreFact, from 11 recent human annotated datasets on fact-checking and grounding LLM generations. Bespoke-MiniCheck-7B is the SOTA fact-checking model despite its small size.