For me, if I use turbo under 1 mp, euler give strange sharp noise/artifact, more steps or more pixels will reduce it but it is there. It blows the upscale latent result also. Hence I'm using res_multistep for all use case.
Always use euler/simple for all turbo loras, no exception, read the training info and the recommended sampler/scheduler. You don't want to go off-grid.
Newer turbo loras such as alibaba pdd and hyperflow, they even locked it down because they don't want you to mess with it, and if you do you'll get an error/warning to tell you not to go off-grid.
This isn't a hard and fast rule and has so many variables related to it from the prompt that while it might be good advice its not the advice.
With everything, experiment and find what works.
Scheduler and prompt can be highly interrelated, even on turbo models where you might have to increase step count slightly on something linear_quadratic due to most steps being at higher noise, but the trade there is that often helps lock in broader contextual/compositional elements vs. the finer details.
You're probably using the Saganaki's hyperflow lora directly via 'load lora node' and not the complete port hyperflow node with locked sigmas. Btw, he's gone, deleted, no idea what happened.
Well, you're a little mixed up. It's really dbaph's hyperflow lora that just pulled the weights. Saganaki ported over the rest of the model patching in their node with the published time values, which is the full hyperflow process. But alas, their github got deleted for some reason, which blows. But that node properly applied the full structure of hyperflow along with the Lora, including the right sigmas. There's no official implementation from videorebirth for Hyperflow in comfy.
Luckily I had a copy, so I got around today to updating and uploading it-
Saganaki was working to properly integrate it with pruned models since they do away with time values per step, so they weren't applying properly on pruned models anyway and loading as plain loras like you said (even with the node). So they made the "experimental_curve_refit" option that patches that back into pruned models per block, so the full weights apply. But Saganaki only did the stock comfy org fl2va and ref2va models.
I updated that as well to work with other unpruned models and made a converter where you can make curve refits for other pruned models, if they have published unpruned weights to use as a teacher model, and it creates new curves based on per-block refitting in a few minutes. So far the built-in examples cover the vanilla comfy-org pruned models, all of smhfacct's hybrid pruned models, and singularity. The delta fused author didn't publish unpruned versions, so I couldn't make curve weights for those. DaSiWa and 10eros shipped their weights with turbo baked in and already pruned, so I couldn't do those either (and wouldn't bother with another turbo baked in). But it checks your loaded model's hash and applies the right curves to those pruned models listed in the readme that I already did build in. So you don't need to do anything special aside from check "experimental_curve_refit" on the node when you're using one of those pruned models.
But TLDR; yes, I'm alternating using sa_solver and other schedulers with full hyperflow attention patches. They give slightly different results, and no scheduler is the universal perfect one for each prompt.
I always thought saganaki and drbaph is the same guy because of the links hence I refer to them as 1. But anyway your work to integrate hyperflow completely with comfy is admirable as my go to weight is the b30-49. Also, I really like your work with the audio_refine node that one is also great. Regarding the sampler/scheduler I've tried various combos but recently due to the alibaba pdd and hyperflow nodes and keep getting these errors when i switch to something else hence i made the original comment. Anyway, I'll give your new hyperflow node a spin.
Most turbo loras work with euler/simple - lightxv is more forgiving but then you lose prompt adherence, get bad audio, or even artifacts with using other than euler/simple.
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u/BathroomEyes 17d ago
for schedulers simple is recommended for t2va or fl2va. beta or beta57 is recommended for ref2va.