license: mit
datasets:
- AbstractPhil/geometric-vocab
pipeline_tag: zero-shot-classification
Pentachoron Geometric Feature Extraction
Pentachora VIT are essentially micro-sized feature extractors that provide substantial accuracy for their small size. The more experiments I run, the smaller they become. The final goals to be a full clip-vit that can house the entirety of laion 400m in a fraction of the size and compute as OpenAI's clip-vit line. After this point I'll be confident the math is lined up well enough to train the true flagship - Beatrix.
The process of useful classification and feature extraction has been a non-trivial problem in the Computer Science industry for a long time.
This repo will house the various vit experiments that I frankenstein together; manifesting their weights and model codes in the repo itself.
As I am an independent researcher my resources are limited and I don't have the backing of any donors, so there will be time gaps unless some hardware is sliced off for me.
Many of my repos have certain elements omitted purposely for papers in writing, my thesis arguments, my statements about certain universal elements, and a multitude of other ramblings that I don't plan to release specific key details in full phonebook fashion for just ANY PERSON to read.
Let me use your high-end hardware. I deliver - success or failure, but I will deliver.
I will not rattle a tin cup for you. Work out a deal with me and you get the weights - I get the classes developed for further use, meant for public release.
Let me know if you're willing to work with me. I'll gladly share the code, the process, the progress, and the built accumulated warchest of potentials that this system entails if you provide me gateways to some hardware that I can utilize.
Until then, one experiment at a time.