Evaluate LLMs for RAG with LLMWare

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Learn how/why we evaluate LLMs for RAG using our open source RAG Instruct Benchmark Test sets in Hugging Face. Please subscribe for more content!

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Комментарии
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this is beautiful content! exactly what I was looking for but summarizing this work in a blog with evaluation table and some diagram of the workflow of the benchmarking would have been great.

amrohendawi
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Very rightly said at 5:08, I have been struggling to train OpenAI 3.5 turbo to handle "Not Found" scenarios. It always make up something, even after I have given it explicit instructions not to do so. I am using the RAG approach currently, but seems like I need to switch to the "Fine Tuning" approach.

Glimmer-t
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Thanks for this informative video, will try it out

gw
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I wonder if all these companies trying to hire consultants to put together these custom LLM solutions will be turned off by the whole idea once they figure out that they only thing they're good for is basically sounding like they have an answer, and not want to try again when capable models, maybe in a few years time come out.
Sort of like what happened with IBM 'Watson' - where it couldn't actually do anything useful, but every large business found that out the hard way 8 years ago.

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