FlexGen VS IOPaint

LLaMA, Pythia, RWKV, Flan-T5 (self-hosted), FlexGen

> With no real knowledge of LLM and only recently started to understand what LLM terms mean, such as 'model, inference, LLM model, intruction set, fine tuning' whatelse do you think is required to make a took like yours?

This was mee a few weeks ago. I got interested in all this when FlexGen (https://github.com/FMInference/FlexGen) was announced, which allowed to run inference using OPT model on consumer hardware. I'm an avid user of Stable Diffusion, and I wanted to see if I can have an SD equivalent of ChatGPT.

Not understanding the details of hyperparameters or terminology, I basically asked ChatGPT to explain to me what these things are:

   Explain to someone who is a software engineer with limited knowledge of ML terms or linear algebra, what is "feed forward" and "self-attention" in the context of ML and large language models. Provide examples when possible.

„Inpaint anything“ and „cleaner“ extension can remove text or anything you mark, if you are on A1111 webui, you can install them from extension tab. Standalone , there is lama cleaner , https://github.com/Sanster/lama-cleaner

This is an app developed from my other open source side project Lama Cleaner.

When you're training, the model learns things you don't prompt for, like the face you want, but it also learns things that don't change much, even if prompted. So if there is a necklace there, it'll learn that something goes in the neck area. You might look into Lama Cleaner to remove the necklaces without messing anything else up.

I prefer Lamar Cleaner: https://github.com/Sanster/lama-cleaner to anything built into A1111.

I use Lama Cleaner for stuff like this. Works great and supports all the SD models + Segment Anything, etc etc etc : https://github.com/Sanster/lama-cleaner