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Your intuition about this is not accurate. 24GB is more than enough for running local image generation and training a LoRA. You also don't need an insane amount of data; a LoRA is generally trained with less than 100 images, usually around 15-30 images.
To do deepfakes, you're not training an entire brand new image model from scratch, which is only within reach of big organizations, you're just adapting an existing model that is publicly available. You can do this for free with open source tools. It is within reach of anyone with high-end gaming hardware or anyone willing to pay for some cheap cloud compute.
Further, LoRAs for most celebrities and famous people have already been trained and can be found on the internet for free, so the training step is likely not even necessary in most cases.
If this is the case, then images generated with the same expression in the same light will not look out of place.
But you will still be able to generate images with other lighting and facial expressions, even without sample images for them, because the base image model that is being adapted already "understands" differing facial expressions and lighting and can apply them to the subject of the LoRA, in the same way that it can combine random concepts together to create something "new" that wasn't present in the training images (eg a painting of a zombie unicorn in the style of a specific painter)
Yeah I'll be honest - I understand nueral networks, but don't understand pretty much any actual implementarion of them.
It's good to know that 24GB is big enough for something tho so maybe I can find AMD support to learn LLM shit anyway.
But thanks for that information, makes it a bit more... Uncomfortable in context.
AMD GPUs are well supported by many LLM frameworks. I'd recommend ollama