My previous experiments with Stable Diffusion have used an older (and smaller) version: 1.4. The most recent version available is 3.5. There have been a lot of changes so I wanted to see if image generation itself had improved much.

This is the model_id and pipeline to use for this:

model_id = "stabilityai/stable-diffusion-3.5-medium"
device = "cuda"

pipe = StableDiffusion3Pipeline.from_pretrained(model_id, dtype=torch.float16)
pipe = pipe.to(device)

This model weighs in at 16 Gb on disk, so be prepared for a wait, but once it is in your cache it is just a few seconds to get it into memory.

My overall plan here is to investigate morphing one face into another. I had been using 1.4 which is nice and light, but got quite blurred results for the intermediates. Not much better than just tweening pixel intensities I would say. This is why I made the jump to the bigger model. However I won't be doing many experiments with 3.5 as it is just too compute hungry. My small gpu on my laptop took 25 minutes to produce a single image based on this code.

prompt = "a photo of an astronaut riding a horse on Mars"

image = pipe(prompt).images[0]  

And this is a version from 1.4

So pretty much worth the wait. A big leap in image quality and the prompt is extremely basic too. The hardware I have is just not suitable for this level of model, but the result shows what can be done with open technology.