3 ms·

I tested a bit and the quality for photorealistic images is surprisingly bad, and definitely worse than LCM and of course normal SDXL. For more artistic images,

I tested a bit and the quality for photorealistic images is surprisingly bad, and definitely worse than LCM and of course normal SDXL. For more artistic images, SDXL Turbo fares better. Unlike normal SDXL, you're required here to use the old-fashioned syntatic sugar like "8k hd" and "hyperrealistic" to align things.

jauntywundrkind 3y ago
Are there any good resources for learning a lot of "syntactic sugar" terms? This is new to me, but I'd love to know more.
- swyx 3y ago
  https://github.com/swyxio/ai-notes/blob/main/IMAGE_PROMPTS.md https://github.com/swyxio/ai-notes/blob/main/IMAGE_PROMPTS.m...
  - jauntywundrkind 3y ago
    #LearningInPublic strikes again! I love you swyx!
    - swyx 3y ago
      haha thank you ser. best way to thank me is to start your own LIP practice and pass it on :)
- genewitch 3y ago
  It is completely dependent on the model. Civit dot ai has model showcases as well as fine-tune showcases, and you can click any image or press the (i) to see the generation info. Some models like natural language prompts - "draw me a pterodactyl tanning at a beach", some prefer shorthand (danbooru style clip) - "1man, professor, classroom, chalkboard, white_hair, suit", and some work with a mixture of the above as well as the syntactical sugar -"masterpiece, 8k, trending on artstation, space image, a man floating next to a spaceship in space, bokeh, rim lighting, cinematic lighting, Nikon D60, f / 2" Fine-tuning models - LoRA, etc, allow one to convert prompts from one style to another if they wish, but usually it's to compress an idea, style, person, object, etc in to a single "token", so you can work on other aspects of the image. Check out civit AI and you can sort of get an idea of the cargo cultism as well as what sort of keywords actually make a difference.
  - dragonwriter 3y ago
    > Civit dot ai The site you are thinking of is https://civitai.com/ https://civitai.com/ not "civit dot ai".
dragonwriter 3y ago
In my own testing (using ComfyUI), the best of the "fast gen" techniques for sdxl is using the Turbo model [0], but using the LCM sampler with the sgm_uniform scheduler (which is normal for LCM) with it, and running it up to 4-10 iterations instead of just one. I think StabilityAI demos are using Euler A with the normal base scheduler, and running a single iteration (which is cool for a max-speed demo, and its awesome for that speed, but its leaving a lot of quality on the table that you can get with a few more iterations especially with the LCM/sgm_uniform sampler/scheduler combo.) Bumping CFG up slightly helps, too (but I think adds another performance hit, because I think the demos are running at CFG 1, which AIUI disables CFG and reduces computations per iteration.) > Unlike normal SDXL, you're required here to use the old-fashioned syntatic sugar like "8k hd" and "hyperrealistic" to align things. That's not "syntactic sugar", and its not particular my experience that it is needed with sdxl turbo. [0] actually, differencing the base sdxl model from the turbo model to get a "turbo modifier", and then combining that with a good SDXL-based checkpoint, because StabilityAI's base models are pretty ho-hum compared to decent community checkpoints derived from them, but that is kind of a peripheral issue.

jauntywundrkind 3y ago

Are there any good resources for learning a lot of "syntactic sugar" terms? This is new to me, but I'd love to know more.

swyx 3y ago
https://github.com/swyxio/ai-notes/blob/main/IMAGE_PROMPTS.md https://github.com/swyxio/ai-notes/blob/main/IMAGE_PROMPTS.m...
- jauntywundrkind 3y ago
  #LearningInPublic strikes again! I love you swyx!
  - swyx 3y ago
    haha thank you ser. best way to thank me is to start your own LIP practice and pass it on :)
genewitch 3y ago
It is completely dependent on the model. Civit dot ai has model showcases as well as fine-tune showcases, and you can click any image or press the (i) to see the generation info. Some models like natural language prompts - "draw me a pterodactyl tanning at a beach", some prefer shorthand (danbooru style clip) - "1man, professor, classroom, chalkboard, white_hair, suit", and some work with a mixture of the above as well as the syntactical sugar -"masterpiece, 8k, trending on artstation, space image, a man floating next to a spaceship in space, bokeh, rim lighting, cinematic lighting, Nikon D60, f / 2" Fine-tuning models - LoRA, etc, allow one to convert prompts from one style to another if they wish, but usually it's to compress an idea, style, person, object, etc in to a single "token", so you can work on other aspects of the image. Check out civit AI and you can sort of get an idea of the cargo cultism as well as what sort of keywords actually make a difference.
- dragonwriter 3y ago
  > Civit dot ai The site you are thinking of is https://civitai.com/ https://civitai.com/ not "civit dot ai".

dragonwriter 3y ago

In my own testing (using ComfyUI), the best of the "fast gen" techniques for sdxl is using the Turbo model [0], but using the LCM sampler with the sgm_uniform scheduler (which is normal for LCM) with it, and running it up to 4-10 iterations instead of just one. I think StabilityAI demos are using Euler A with the normal base scheduler, and running a single iteration (which is cool for a max-speed demo, and its awesome for that speed, but its leaving a lot of quality on the table that you can get with a few more iterations especially with the LCM/sgm_uniform sampler/scheduler combo.) Bumping CFG up slightly helps, too (but I think adds another performance hit, because I think the demos are running at CFG 1, which AIUI disables CFG and reduces computations per iteration.) > Unlike normal SDXL, you're required here to use the old-fashioned syntatic sugar like "8k hd" and "hyperrealistic" to align things. That's not "syntactic sugar", and its not particular my experience that it is needed with sdxl turbo. [0] actually, differencing the base sdxl model from the turbo model to get a "turbo modifier", and then combining that with a good SDXL-based checkpoint, because StabilityAI's base models are pretty ho-hum compared to decent community checkpoints derived from them, but that is kind of a peripheral issue.