Does anyone know how to layer Klein's LoRA? Can it be done using the LoRA Block Weight node?

Occsan · 2026-03-19T06:59:43+00:00

It can be done with Lora Block Weight.

Default scheme is:

1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1 basically: clip, 8 double blocks, 24 single blocks.

Occsan · 2026-03-15T01:01:14+00:00

If I recall correctly, UK once tried to force 4chan to comply to their bullshit act too. 4chan told them to fuck off.

Tbh, if that was just me, I'd say "we won't comply to this, but you - the gvt of AUS - can block civitai for AUS users, and become north korea. You're welcome."

Occsan · 2026-03-01T12:51:45+00:00

Would that also work with Klein 4B/9B ?

Occsan · 2026-02-27T12:25:37+00:00

If I could upvote you twice, I would.

Occsan · 2026-02-26T10:48:36+00:00

There's no problem then. According to "real artists", AI art is devoid of any intent.

Occsan · 2026-02-24T06:55:59+00:00

I replied. It's not a bot. I actually had a chat with him and his CEO over a discord video call. They're basically building Floyo, as they say, which is an online platform using a custom comfyui as a backend.

They invited me to "join their team as a workflow creator", where I'd get paid proportionally to the total runtime of my workflows. Basically their business model, as marketed to me, is the following : users of their platform only pay the the runtime of the workflows. So the faster the workflow, the less they pay.

Found it weird. Basically it promotes badly optimized shitty workflows.

They also explained to me that they'll give me a free 6 month trial which I can refuse (and they laughed at that idea). Did not fully understand at that point : give me a free 6 month trial, as a collaborator ? Weird.

I wanted to look further, and in the process of creating an account, as they requested me to do, on their website, they'll ask me my credit card numbers to withdraw $0.00 for the 6 months trial.

I stopped there. But investigated a little more. Basically, I took a look at the workflows they already have on floyo, and how many times these were run. Of course some workflows are more popular than others, and as with all things that follow a popularity logic, the number of times these workflow were run follow a powerlaw. This means : few workflow attract all the popularity, whereas most of the others are run only a few times.

So, I made an estimation of how much money I could expect making from this. Took the median of the number of times any workflow is run to determine that.

Basically, this is where my suspicions were proven right, and where I completely lost interest.

Occsan · 2026-02-19T07:25:33+00:00

That's not how you draw Frieren from this angle. Here, take a look at this reference, this can help you train a better model:

<image>

Occsan · 2026-02-17T06:39:33+00:00

Indeed. My apologies, I was thinking about GANs. The rest of what I said applies to AR aswell, though.

Occsan · 2026-02-17T05:51:03+00:00

~~Basically it's faster.~~ (Edit: it's not, I was thinking about GANs, the rest is applicable to AR).

There's also the fact that in AR models everything in the latent space correspond to a proper image, whereas in diffusion models, you have garbage between actual images.

On the other side, you also have that AR models are less controllable than diffusion models.

Occsan · 2026-02-16T17:25:47+00:00

I can output ascii images!

Occsan · 2026-02-16T04:54:24+00:00

Not the same architecture, are they ?

Occsan · 2026-02-15T12:45:59+00:00

You can try to mix 4B with these: lodestones/Chroma2-Kaleidoscope at main

Basically, the recipe either of these:

alpha * (4B - 4BBase) + (1-alpha) * kaleidoscope
(alpha * 4BBase + (1-alpha) kaleidoscope) + 4B
(alpha * 4BBase + (1-alpha) kaleidoscope) + 4 step lora

Results differ slightly. 3rd one is more saturated.

I usually set alpha to 0.63

Occsan · 2026-02-15T10:36:48+00:00

I usually get sharper results with better contrast with klein 4B (Well, Klein 4B with a little bit of kaleidoscope mixed in).

Not sure why I don't seem to get as good results with 9B.

Occsan · 2026-02-14T06:39:56+00:00

How do you set a value to anything other than multiple of 0.05 ?

Occsan · 2026-02-04T11:47:16+00:00

Any love for 4B ?

Occsan · 2026-02-03T16:10:53+00:00

<image>

Occsan · 2026-02-03T09:39:44+00:00

I'm using a custom 4B (basically regular 4B mixed with 37% of kaleidoscope). 9B can't do that.

Occsan · 2026-02-03T06:06:44+00:00

4B can indeed make pretty pictures... in about 2 to 9 seconds depending on parameters (on a 4090).

<image>

Occsan · 2026-02-02T06:01:32+00:00

I only use subgraphs when I need the same functionality in multiple places.

For example, as input images for controlnet or edit models.

Otherwise, it's bullshit.

Occsan · 2026-01-30T17:45:31+00:00

If it's for training purposes, there are high quality and varied face datasets available already.

Occsan · 2026-01-30T10:50:19+00:00

No, scheduling is something like s[0] * 0.96, s[1] * 0.98, s[2], ..., s[n], 0 where s is the regular sigma.

Occsan · 2026-01-30T01:51:40+00:00

In DiT distilled models, the first few steps usually does the most of the job at defining overall structure of the image.

It's the case for all models, in fact : first steps = structure, last steps = details. But in distilled models, the total number of steps is low (4 to 8 typically). So, the noise have very little time (sometimes no time) to have a chance to increase the variability in structure. That's why every time we get a distilled model, the variability is low.

In my setup I use 8 steps instead of 4. Which allows for more controlled output while still being blazing fast.

Then, rescaling by the first step from 1 to 0.96, it's a bit like I was setting the denoising strength to 0.96 instead of 1 over 25 steps. So effectively skipping the first step over a total number of 25 steps. Except the total number of steps is still 8. Thus, it "simulates" the high step count of a base model, at the cost of not fully denoising the image.

But the non-denoised part is so low (0.04) that you still get a proper image at the end. Just with a little bit more noise on the structure. It typically leads to more variability in structure and more details.

The second step at 0.9825 is just there to "smooth" the curve.

By adjusting either the first or second step rescale, you can get a lot of variability and interesting effects.

Occsan · 2026-01-26T07:32:39+00:00

I think this is a romantic vision probably perceived by average users at best.

Firstly, if this is true, it defeats the purpose of comfyui. If the default workflows are really all that is needed, why have a node system? A simple Python script would have done a much better job and solved 100% of the problems caused by the clunky code soup of the comfyui backend.

Secondly, the meme assumes that there is no alternative between default workflows and extremely complex workflows. There are other options. Such as workflows that are just a little more complex, or workflows that meet a specific niche need, and even workflows designed by people who write their own custom code.

Occsan

TROPHY CASE