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m-ricย 
posted an update Jul 25, 2024
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๐—”๐—ด๐—ฒ๐—ป๐˜๐—ถ๐—ฐ ๐——๐—ฎ๐˜๐—ฎ ๐—ฎ๐—ป๐—ฎ๐—น๐˜†๐˜€๐˜: ๐—ฑ๐—ฟ๐—ผ๐—ฝ ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ฑ๐—ฎ๐˜๐—ฎ ๐—ณ๐—ถ๐—น๐—ฒ, ๐—น๐—ฒ๐˜ ๐˜๐—ต๐—ฒ ๐—Ÿ๐—Ÿ๐—  ๐—ฑ๐—ผ ๐˜๐—ต๐—ฒ ๐—ฎ๐—ป๐—ฎ๐—น๐˜†๐˜€๐—ถ๐˜€ ๐Ÿ“Šโš™๏ธ

Need to make quick exploratory data analysis? โžก๏ธ Get help from an agent.

I was impressed by Llama-3.1's capacity to derive insights from data. Given a csv file, it makes quick work of exploratory data analysis and can derive interesting insights.

On the data from the Kaggle titanic challenge, that records which passengers survived the Titanic wreckage, it was able by itself to derive interesting trends like "passengers that paid higher fares were more likely to survive" or "survival rate was much higher for women than men".

The cookbook even lets the agent built its own submission to the challenge, and it ranks under 3,000 out of 17,000 submissions: ๐Ÿ‘ not bad at all!

Try it for yourself in this Space demo ๐Ÿ‘‰ m-ric/agent-data-analyst

Wow!! Is all I have to say. The ReAct framework is simply a game changer.

Thanks so much for this demo. I've made my own implementation of it here. Please check it out and let me know what you think.
https://huggingface.co/spaces/dkondic/data-analyst

I've made it a bit more general with the base prompt so the user can input specifics in their own input, or just ask a simple question.

I did notice the max token is 8.2 k even with llama3.1. Is that by design or a bug somewhere?

I'm also having a hard time understanding the difference between the code agents and agents. Would you be able to provide some insight on those?

Thanks again!