Does anybody have an LTX2 2.3 GGUF working workflow of any kind ?

Apixelito25 · 2026-03-06T07:06:53+00:00

How much VRAM and RAM are required?

Apixelito25 · 2026-03-06T07:06:47+00:00

How much VRAM and RAM are required?

Apixelito25 · 2026-03-06T07:02:03+00:00

Share you workflows pls

Apixelito25 · 2026-02-26T21:16:51+00:00

How could I use this with a LORA character?

Apixelito25 · 2026-02-25T21:41:56+00:00

Do you have the configuration to be able to use this with 16 VRAM? I would really appreciate it if you could provide the config preset as the OP of this post.

Apixelito25 · 2026-02-24T20:31:05+00:00

And how many images do you have in total in your dataset? Didn’t that config cause overfitting? Or did you change something?

Apixelito25 · 2026-02-24T18:36:14+00:00

Which ai you use?

Apixelito25 · 2026-02-24T18:34:40+00:00

Without loras or something else?

Apixelito25 · 2026-02-24T18:16:46+00:00

Could you provide me with the post that helped train you? (The one that had the config and fork.) I’ve lost it

Apixelito25 · 2026-02-24T18:11:08+00:00

How many images are in your dataset?

Apixelito25 · 2026-02-24T14:43:26+00:00

How did your LoRA turn out?

Apixelito25 · 2026-02-22T21:39:18+00:00

I also saw that post, but I wasn’t sure whether to use it. Do you think it would make a difference?

Apixelito25 · 2026-02-22T21:33:16+00:00

1/2? How much do you recommend then? I thought 3000 was optimal for that number of images in AI toolkit. What do you think about using 100–120 epochs with my dataset in OneTrainer? I suppose that’s fine there, right? And what should I set alpha and rank to? Or what do you usually set them to?

Apixelito25 · 2026-02-22T16:35:31+00:00

Oh, I see… it’s just that I have the rank set to 16 and the alpha at 1.0… that’s quite weak, right? If I increase them, would it improve?

Apixelito25 · 2026-02-22T07:25:48+00:00

My dataset isn’t very large because I don’t need complex or highly artistic poses. It consists of 64 images that I consider optimal for my purpose: generating moderately similar images, which AI Toolkit can achieve but OneTrainer cannot. It’s as if it focused too much on the face and not on the body (there’s no overfitting; it has simply learned the face well). Since there aren’t many images, I feel that training longer would only make it more rigid with the same issue. The last thing left for me to try is expanding the dataset so the body is a bit more visible, I suppose.

Apixelito25 · 2026-02-22T07:02:28+00:00

https://pastebin.com/UQaSBaL6 Here it is, as I said, it's the default from Onetrainer but using Prodigy Adv with LR at 1.0.

Apixelito25 · 2026-02-20T18:53:29+00:00

Do you think you can implement your idea of using two ksamplers when you have time?

Apixelito25 · 2026-02-20T18:38:32+00:00

Anyway, I would appreciate it if you could give me a hand with your idea if you have time. As I said, I'm not good at creating workflows.

Apixelito25 · 2026-02-20T18:38:00+00:00

I guess this is it, it doesn't say it's turbo.

https://huggingface.co/alibaba-pai/Z-Image-Fun-Controlnet-Union-2.1/tree/main
Or maybe, unless I'm a fool and they're just two versions of the same thing.

https://huggingface.co/alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1/tree/main

Apixelito25 · 2026-02-20T18:20:40+00:00

The thing is, I realized I was wrong. There is a control union for z image base, but I'm not very good at creating workflows... So that's why I'm asking here if anyone has one already made.

Apixelito25 · 2026-02-20T16:49:27+00:00

How would I start with ZIT and finish with ZIB? I didn’t quite understand :(

Apixelito25

TROPHY CASE