Llama 3.1 Bespoke MiniCheck 7B This is a fact checking model developed by Bespoke Labs and maintained by Liyan Tang and Bespoke Labs. The model is an improvement of the MiniCheck model proposed in the following paper: 📃 MiniCheck: Efficient Fact Checking of LLMs on Grounding Documents , EMNLP 2024 GitHub Repo The model takes as input a document and a sentence and determines whether the sentence is supported by the document: MiniCheck Model(document, claim) {0, 1} 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. Depending on use cases, adjusting chunk size may yield better performance. Llama 3.1 Bespoke MiniCheck 7B is finetuned from internlm/internlm2 5 7b chat (Cai et al., 2024) on the combination of 35K data points only: 21K ANLI examples (Nie et al., 2020) 14K synthetically generated examples following the scheme in the MiniCheck paper, but with additional proprietary data curation techniques (sampling, selecting additional high quality data sources, etc.) from Bespoke Labs. Specifically, we generate 7K "claim to document" (C2D) and 7K "doc to claim" (D2C) ex…
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