Briefly describing this Streamlit fronted python app that queries against menus pulled from a kaggle uber eats dataset found here. A Streamlit menu search Mini screencast First query something random It is off topic, so no results Continuing from an earlier post, this is taking advantage of Facebook’s BART model. A hugging face pipeline is used to hit against six food and restaurant related topics are averaged and compared against a threshold of 0....

holding pattern Kind of out of the blue, my Withings Body+ screen is on but theres nothing there. After some reseting, also cannot connect by phone. Removed it from the Withings app on my phone, trying to reconnect the scale as a new scale, but searching for the device, I see the Body+ c0 pop up, I select it, but then I am right back to the search for device screen....

Let’s look at what bart-large-mnli has to say on restaurant related labels for food and non food queries The queries here are just arbitrary statements I came up with off the top of my head. You can skip to the final scoring, but in summary, using a super simplistic evaluation here, I think that the super accessible bart-large-mnli model does pretty well here. One observation I am seeing casually, which I believe Jake Tae https://jaketae....

What to do with the left over rubber from your Xero DIY haraches? I originally got this Vibram rubber sheet from this xeroshoes.com link, a few years ago. I have made two pairs for myself and I made a few pairs for some family members too. They are great, however, I had stowed away the left over rubber for, well, a long time now haha. I didn’t know what to use the left over material for, until now 😀....

Ok fasting hours, but how about eating hours? The data dump from my Zero fasting app highlights the fasting hours. I had used Zero from 2019 to late 2023, and I wanted to look at briefly, well what about the eating hours, other than the fasted hours? In an effort to save time, I used ChatGPT to come up with the calculation around the eating hours. Actually the first try was interesting since the outcome was showing daily eating hours that were beyond 40 hours 😅, but coercing ChatGPT to try to correct so this falls within the expected under 10 hours, ChatGPT was able to actually course correct nicely !...