visual-chatgpt VS ControlNet

For prompting, the GitHub repo I refer to the most is actually one from Microsoft: https://github.com/Microsoft/Visual-ChatGPT

Found relevant code at https://github.com/microsoft/visual-chatgpt + all code implementations here

Github: https://github.com/microsoft/visual-chatgpt/tree/main/LowCodeLLM will soon be available!

It's not so much the size of the LLMs, it's what people are able to do with them in novel ways, e.g. https://github.com/microsoft/visual-chatgpt/tree/main/TaskMatrix.AI

There is a python library langchain, which microsoft used to give it access to image editing tools. You can write your own tools for it very easily, I've been having fun with it. I gave it internet search tools and it worked great at using current events in the response.

Something like this: https://github.com/microsoft/visual-chatgpt/tree/main/TaskMatrix.AI could enable a far simpler AI to start making copies of itself.

Reminds me of VisualChatGPT (https://github.com/microsoft/visual-chatgpt), which also uses a LLM to decide what vision models to run.

The best Microsoft API or overall API? It really depends what your goal is. https://github.com/huggingface is great if you want to dive right in, but https://github.com/microsoft/visual-chatgpt might be good as well (not easy to get to work locally).

It`s all possible. Have a look into Automatic1111`s Web UI, ControlNet, OpenPose and, if you don`t have a dedicated GPU with at least 8GB of VRAM, or at least 16GB of RAM to use the CPU, you can also use Stable Horde to use the webUI with a peer-to-peer connection, where you`ll only use a fraction of your resources, but you`ll be able to use local AI models with all the bells and whistles that you won`t get from "state-of-the-art" paid services.

Next up is ControlNet. Controlnet, as Illyasviel--creator of controlnet--describes it, "let's us control diffusion models!." ControlNet is a neural network structure to control diffusion models by adding extra connections. [8]. There is more to that than what I described, but the big take-away is that ControlNet takes a preprocessed image that you provide (or is generated) and uses that as a way of constraining the output the sampler's noise generates, allowing you to have a bit more control of the output. ControlNet is typically used for character or scene "artwork", which previously would have been a challenge with just prompting alone (at least with this current architecture).

For your first part of the comment, I can simply refer you to technologies like ControlNet, LoRA and prompt embedding: https://github.com/lllyasviel/ControlNet https://github.com/microsoft/LoRA

Here you can see what every controlnet preprocessor and model do, to give you an idea of ​​how to use

Ya, it takes awhile to really start getting comfortable with the wonkiness. If you are trying to do something specific, look for a LoRA, but in general I'd recommend you get controlnet so you can feed it a reference image. Another simple trick is to edit the image a bit in GIMP or a photo editor to get the color scheme you like and then feed it back to img2img at low denoising (0.1-0.2) to refine it. You can also add just garishly bad cartoon drawing or photoshop in assets and img2img will usually make something of them and blend them into your image, I find this easier than using img2img scribble.

If there are no errors, go to the "Extensions" tab, then "Install from URL". There, enter "https://github.com/lllyasviel/ControlNet" then click "Install".

This is a good place to start reading. Given the open-source nature of SD, there are setups of various difficulty available. A1111 is the "standard" people enjoy because it's easy to plug in new stuff (ControlNet, new models, etc.), but it's not inherently easy to set up and get going. There is an installer for it, but I haven't tried it.