Projects using pandas in Oregon
Projects using pandas in Oregon
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Guy G
Each pulse consists of the changes needed to transform the visualization of one subject range to another. I could reduce the pulsing by using inter-prompt interpolation but at the time I made these last year the computational overhead was too expensive. If I had the time to do it now it would be quite a bit more efficient on an A100 for about the same cost including interpolation. This is a visualization of a couple months worth of "Physical Review Letters E" which is very much worth checking out.
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Guy G
Another fun project I started last year is called "CASI" for Cyclical Adversarial Step-wise Improvement. It leverages the fact that when LLMs engage in self-correcting loops they get better at a task. In this case we are pitting 2 models and 2 system prompts with distinctly different purposes against each other to improve a concept or idea. This is unlike self-play and more like other-play. I would love to include an intermittent training pass or LoRa construction between cycles to make the models focus more completely. CASI is still a work in progress so use at your own frustration. If you encounter any issues please log them with the github repo, you will be helping the entire world :) https://github.com/TheOneTrueGuy/CASI
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Guy G
Language models provide some spectacular new opportunities for discovery. While working on some ideas it occurred to me to explore the relationships between concepts spatially. Interpolating across the latent space between concepts and then mapping to a vectors nearest token predicate. I arranged this formulation as a form of tessellation to cover the n-dimensional volume efficiently. The result is a work-in-progress I call the Tessellator. Since this is an experiment it just made sense to open source it and a new update is due in the next week or two. https://github.com/TheOneTrueGuy/tessellator
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Guy G
This work was from late last year but I've been meaning to revisit it with an Agentic twist. Rebuilt to remain running in real time like a guardian I think it could be truly useful. It got open-sourced in this form after the client decided not to pursue it further. It is a simple tool for analyzing enormous blocks of emails for signs of fraud or deception. It won't take much for me to elevate the performance. https://github.com/TheOneTrueGuy/Fraud-Analysis-Tool and here is the video that was made for the associated Kaggle contest: https://www.youtube.com/watch?v=do9uPzW4AVk
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Guy G
AI-Powered Fraud Detection Platform for Kaggle Contest
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