vishal @vishal_learner
https://t.co/tSqI2ObecS Maintainer. https://t.co/gFYvT1B8or community member. Will post about sports occasionally. #FlyEaglesFly youtube.com/@vishal_learner Joined August 2023-
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vishal retweeted
and BRIGHT, ReasonIR, and Reason-ModernColBERT definitely up there too. I also really liked the depth of the studies in TU Wien's Active Learning paper
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vishal retweeted
I'll go first: ColPali is super cool. So is LITE, learnable late interactions.
vishal retweeted
These findings are very similar to what we found in the full experimental suite when developing QLoRA (>1500 experiments). Long story short: LoRA/QLoRA works well, is cheap on low-memory devices, and allows multiple cheap deployments.
These findings are very similar to what we found in the full experimental suite when developing QLoRA (>1500 experiments). Long story short: LoRA/QLoRA works well, is cheap on low-memory devices, and allows multiple cheap deployments.
vishal retweeted
IIUC they didn't use DoRA, so the results can be even better than shown here:
IIUC they didn't use DoRA, so the results can be even better than shown here:
vishal retweeted
If a voken is a visual token, a speech token is a spoken.
If a voken is a visual token, a speech token is a spoken.
vishal retweeted
TIL about Monkey which is an approach to allowing high resolution image inputs
vishal retweeted
TIL about Lumos which uses Scene Text Recognition (STR) to extract text from images up to 3000x4000 pixels in resolution
vishal retweeted
This concept makes sense and I don't recall hearing/seeing it before: does a task really count as "zero-shot" if the model was trained on it "in some indirect way"?
vishal retweeted
In 285 days, my current role as a data analyst will come to an end. I’m excited to begin my professional machine learning journey. Just published a blog post on what I’ve been building, learning, and looking for next (link below).
vishal retweeted
On the importance of data when training VLMs (from Meta's Introduction to Vision-Language Modeling)
vishal retweeted
i love how masking always seems to be surprisingly effective (from Meta's Introduction to Vision-Language Modeling's "Speeding up training" section)
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