I got bored last night and took a look what is out there. Between diffusion and GAN workflows, you can deepfake almost anything you want in any style with just a little technical background.

You can easily take a real photo and use inpainting to replace any aspect of the image, then run it through a few img2img loops to balance the composition. You can train a subject finetune with a handful of pictures and a few hours of training time.

You can use consumer face swap tools to swap faces into any image you want.

Midjourney v5 can generate images that are hard to differentiate from real photos.

From my understanding its limited to no commercial use, so you can use it for what you need, but not commercially.

Maybe, open assistant by Stability.ai is doing this type of manual dataset collection. The training data and the model weights are supposed to be released once training is complete

The license won’t change. The dataset was collected in a way that violates the term of service of OpenAI, which they used to generate the data. If they allowed commercial use it would open them up to lawsuit.

The use of OpenAI’s models for generating competing models violates the term of use, which is why the Stanford dataset is restricted.

https://github.com/oobabooga/text-generation-webui

I’ve had great results with this interface. It requires a little tweaking to get working with lower specs, but it utilizes a lot of optimization options including splitting the model between VRAM and CPU RAM. I’ve been running LLaMa 7b in 8bit and limiting to 8GB of VRAM.

Looking forward to it! I’ve been doing style training on the lastBen colab but I have a lot of artists that want a more accessible way to build and use models based on their own styles

Does your api support the ability to train a style instead of a subject?

Meta is crashing because of C level hubris and the belief that they could be the central point of all social interaction online and in the metaverse. They've been making poor decisions internally for years and its catching up to them.