Hyper-SD is one of the new State-of-the-Art diffusion model acceleration techniques. In this repository, we release the models distilled from SDXL Base 1.0 and Stable-Diffusion v1-5
Project Page: https://hyper-sd.github.io/
Original Repo: https://huggingface.co/ByteDance/Hyper-SD
Original Paper: https://arxiv.org/abs/2404.13686
Description
FAQ
Comments (24)
I didn't have much luck w/ this 4-step LoRA (would love to see some examples posted) - I downloaded their 4/30/2024 8-step from Hugging Face and it works for me wrt getting crisp results.
Just to be clear: the 8-step CFG (Hyper-SDXL-8steps-CFG-lora.safetensors, also here) LoRA worked okay for me.
May I ask if there are any differences in the image quality generated by the 1-step model, 2-step model, and 4-step model respectively?
@dj9wqurf I am not entirely sure but using with ip adapter you get some crazy results ip adapter is super strong in results
Could you please explain the differences and usage of each of these 5 different versions separately?
how do I use this properly? also the cfg model won't show up in civitai helper, does any one have the text trigger?
Thank you for your work, but can I have more information. You realize that KSampler has more than 10 samplers and sampling methods, how to use your model?
I'm trying to generate an image with 2-10 steps gets just .... (it doesn't work very well:)
You have posted the images, please give us information on what and how. Otherwise we can guess until Chinese Easter.
It is not that hard to find out with a xyz plot. It is a bit model dependent, but I use mostly dpm++3m with the uniform scheduler. For some models 2sa or even euler work better. If uniform doesn't work, try karras. I don't use comfy for plots, but the general approach is zo choose your fav model, a fixed seed, and then put the usual modern samplers on the x axis and the schedulers on y. Use standard resolution and the number of steps the lora is named after with a cfg of 1 and no postprocessing. With 2 or 4 steps per image the whole process is pretty fast.
Edit: 12 step CFG version
There is also a 12 step CFG version available. Would be great if that gets added here as well.
How To Use This? I'm Using This With Forge And It Doesn't Work.
So I tried using this in Automatic1111, but I'm not seeing a difference
Do I just drop the lora in the folder & select it, just as any other lora?
Or do I have to do something like installing nodes/workflow stuff?
I cannot for the life of me get the SDXL CFG 8 Step to work. I'm using comfy. Does anyone have a workflow I can glom off of?
I put sdxl 8-step version in lora file folder, but I could not see it at main interface, what's wrong?
How do you use this?
Set Steps: 8, CFG scale: 3, Sampler: Euler a And Use This LoRA By Tag <lora:Hyper-8steps-CFG-xl:1> It will make the work clearer and faster.
can you make it available to use on civitai generation?
can you make it available to use on civitai generation?
Please guys someone make some stubid proof video tutorial how to use this, in forge... i dont find any info about it... only see comfy ui videos...
Use it like any other LORAs.
Set CFG to 1-2 (CFG 1 is the fastest, almost double speed but negative prompt is ignored). set the steps 4-6 for the 4 steps LORA, 8-10 for the 8 steps LORA ... For higher CFG decrease the strength (0.7-0.9)
Hires fix is recommended.
For the 8 steps CFG version you can use normal CFG like 5-6.
I usually use "Euler A" sampler and "SGM Uniform / Uniform / Beta" schedulers.
Drag this image and drop it in Forge into the prompt field, then press the blue button below the Generate button. Change the lora name in the prompt field to match your file. https://civitai.com/images/42682881
what’s the conversion of steps and scale when this is active is normally? i’ve been using a hyper LoRA for awhile but now i can’t seem to find the right workflow. hypothetically if this LoRA was at 1 weight, CFG scale was at 1.1, and steps at 7, what would be the closest to that without this?
You could try LCM sampler with Karras scheduler along with dmd2_sdxl_4step_lora_fp16 added into the mix, it works pretty darn well imo
It would depend on your model and the sampler you pick so your question quickly becomes meaningless. Also CFG should be 1.0 for the no-CFG ones unless you consciously put up with higher generation times. 7 steps is totally random too. For a given Lora you'll probably get best results by +1 or +2 steps at max, not +3 or -1.
if u use forge/reforge/a1111, go to settings, in search put Lora, and check "Always show all networks on the Lora page (otherwise, those detected as for incompatible version of Stable Diffusion will be hidden)" and now it will show up in lora.
From my test, Euler Beta is the best, Euler A Beta looks good too, but adds artifacts/noise in some generations so is less stable.
This is a complex series of Loras to speed up SDXL.
It's the exact same concept as DMD2 but this one has many more different ones you can download. You probably shouldn't use 1 or 2-step unless you're on some kiosk or something. Higher steps will give you better quality.
This and DMD2 are directly comparable. I'll tell you in advance it's next to impossible to determine which is better, but each one brings out different things from various models.
I will try to explain this, it's not going to be simple:
The No-CFG ones (1,2,4,8 steps) mean the CFG should be 1.0 (in ComfyUi, it might be 0 in other programs, idk). If you set the CFG higher or lower, the generation time significantly increases and it starts interpreting the negative prompt too.
The CFG version 8-steps and 12-steps (not uploaded here, you can get it from Hugging Face) means the CFG is put back in, but the samplers all change and so far my experiments with these have not been a great success. CFG3-4 seems to be good for realism models even though they tell you higher. The generation time is inherently longer than the no-CFG, equivalent to setting a CFG on no-CFG loras.
Getting back to the No-CFG, you have to adjust the Lora strength based on which sampler you choose.
I tested the No-CFG 8-step Lora at 8 steps. This is again, where the CFG is supposed to be 1.0. (That said, I do prefer lower like 0.9 or 0.8 CFG even with the no-CFG ones, but it will increase generation time)
Three combinations I found working:
Euler Ancestral (Euler A, not Euler) - Lora Strength 0.90
DPM++ 2M SDE - Lora Strength 0.60
DDIM - Lora Strength 0.90 (not for realism, it mangles realism too much, but it's interesting)
All these give totally different images, but similar in quality.
The Lora strength is subjective, but if you put it too high for a certain sampler it will quickly overbake your images.
As for scheduler, a bunch of them work, start with SIMPLE, then NORMAL is very similar too. You can try them out. (Whatever you heard elsewhere will not necessarily work well on this one, so be sure to test before doing something like Karras or Exponential, those in particular are no good for this one).
That should get you started, good luck and do comment if you can improve on this.
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Hyper-SDXL-8steps-lora.safetensors
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Hyper-SDXL-8steps-lora.safetensors
Hyper-SDXL-8steps-lora.safetensors
Hyper-SDXL-8steps-lora.safetensors
Hyper-SDXL-8steps-lora.safetensors
Hyper-SDXL-8steps-lora.safetensors
Hyper-SDXL-8steps-lora.safetensors
Hyper-SDXL-8steps-lora.safetensors
pytorch_lora_weights.safetensors
Hyper-SDXL-8steps.safetensors
Hyper-SDXL-8steps-lora.safetensors
Hyper-SDXL-8steps-lora.safetensors
Hyper-SDXL-8steps-lora.safetensors
Hyper-SDXL-8steps-lora.safetensors
hyper-sdxl-8step.safetensors
Hyper-SDXL-8steps-lora.safetensors
Hyper-SDXL-8steps-lora.safetensors
Hyper-SDXL-8steps-lora.safetensors
Hyper-SDXL-8steps-lora.safetensors
lightning-hyper-8step.safetensors
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Same model published on other platforms. May have additional downloads or version variants.


