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Ollama Blog更新于 10月14日 09:24

Ollama 上线 Bespoke-Minicheck:用事实核查减少模型幻觉

Reduce hallucinations with Bespoke-Minicheck · Ollama Blog

AI 导读

Bespoke Labs 开发的事实核查模型 Bespoke-Minicheck 已在 Ollama 上线,可对其他模型生成的回答做核查以检测并减少幻觉。它接收文档与待验证的 Claim,若文档支持该 Claim 则输出 Yes,否则输出 No,尤其适合作为 RAG 应用的后处理步骤,确保回答基于检索到的上下文。

正文

当前显示原文,中文全文译文尚未就绪。

September 18, 2024

Bespoke-Minicheck is a new grounded factuality checking model developed by Bespoke Labs that is now available in Ollama. It can fact-check responses generated by other models to detect and reduce hallucinations.

How it works

Bespoke-Minicheck works by taking chunks of factual information (i.e. the Document) and generated output (i.e. the Claim) and verifying the claim against the document. If the document supports the claim, the model will output Yes. Otherwise, it will output No:

RAG use case

Bespoke-Minicheck is especially powerful when building Retrieval Augmented Generation (RAG) applications, as it can be used to make sure responses are grounded in the retrieved context provided to the LLM. This can be done as a post-processing step to detect hallucinations:

For an example of how to use Bespoke-Minicheck in a RAG application using Ollama, see the RAG example on GitHub.

Getting started

Start by downloading and running the model:

Next, write the prompt as follows, providing both the source document and the claim:

Since the source information supports the claim, the model will output Yes.

However, when the claim is not supported by the document, the model will respond with No:

For an example on how to use Bespoke-Minicheck to fact check a claim against source information using Ollama, see Fact checking example on GitHub.

Examples

Model page (Ollama); Model page (HuggingFace); MiniCheck GitHub repository; Intro post about hallucinations and grounded factuality

来源

Ollama Blog