Evaluate LLMs with Language Model Evaluation Harness

In this tutorial, I delve into the intricacies of evaluating large language models (LLMs) using the versatile Evaluation Harness tool. Explore how to rigorously test LLMs across diverse datasets and benchmarks, including HellaSWAG, TruthfulQA, Winogrande, and more. This video features the LLaMA 3 model by Meta AI and demonstrates step-by-step how to conduct evaluations directly in a Colab notebook, offering practical insights into AI model assessment.
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[@TheIITianExplorer]

I love you man, ❤
You are awesome, keep uploading 😊

[@joserfjunior8940]

I LIKE THIS... nice job man !

[@Techonsapevole]

Thanks, great LLM tips

[@bdoriandasilva]

nice! thank you for the video!

[@muhammedajmalg6426]

nice work

[@sagarbhaskar8688]

do we have to add any dataset?

[@A7_-]

Can i do it on llava model

[@abhijoy.sarkar]

How to do it on whole mmlu?

[@krishnapriya9881]

PackageNotFoundError: No package metadata was found for bitsandbytes. I am getting this error even though bitsandbytes is installed and my cuda version is 12.1, please help me with this

[@saumyajaiswal6585]

What about langsmith?It does the same thing right?

[@araara2142]

I need rag chatbot part 2 video, please release, my exam is coming