aifaq.wtf

"How do you know about all this AI stuff?"
I just read tweets, buddy.

#classification

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Synthetic data: save money, time and carbon with open source

February 16, 2024

#synthetic data   #hugging face   #fine-tuning   #performance   #zero-shot classification   #few-shot classification   #classification   #evaluation   #link  

This post does a fantastic job breaking down how you use an expert labeler (teacher LLM) to annotate your data, then use it to fine-tune a student LLM. It's as good or better than crowd workers!

In this case they use Mixtral to prep data for RoBERTa-base, then get equal performance in the end. So much faster! So much cheaper!

Source: https://huggingface.co/blog/synthetic-data-save-costs

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5 learnings from classifying 500k customer messages with LLMs vs traditional ML

July 13, 2023

#classification   #actual work   #shortcomings and inflated expectations   #link  

I love how absolutely bland the results are:

LLMs aren't perfect, but they're pretty good. Fine-tuned traditional models are also pretty good. Be careful when you're putting your data and prompts together. b Life is like that sometimes.

Source: https://www.trygloo.com/blog/classify-text-llms-learnings

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