# Custom BenchMark creation

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**Category:** Intermediate\
**Created:** [January 30, 2025, 9:49am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fcustom-benchmark-creation%2F138079 "2025-01-30T09:49:27Z")\
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**Author:** ![John6666](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/john6666/32/27664_2.png) [@John6666](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FJohn6666)%5C
**Post date:** [January 31, 2025, 5:01am UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fcustom-benchmark-creation%2F138079%2F3 "2025-01-31T05:01:10Z")

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It’s a field I know nothing about, but it seems that Ragas is famous.

> [@Use RAGAS with huggingface LLM](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fuse-ragas-with-huggingface-llm%2F75769)%3A
>
> Hello everybody, I want to use the [RAGAS lib](https://github.com/explodinggradients/ragas/tree/main) to evaluate my RAG pipeline. The evaluation model should be a huggingface model like Llama-2, Mistral, Gemma and more. How can I implement it with the named library or is there another solution? The examples by the team [Examples by RAGAS team](https://docs.ragas.io/en/stable/howtos/customisations/bring-your-own-llm-or-embs.html) aren’t helpful for me, because they doesn’t show, how to use specific Huggingface model. Also a specifc langchain pipeline doesn’t work, because it isn’t the required class. Best regards Christian

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