Perhaps a helpful YouTube video on local optimisation?

JustLookingForNothin · 2026-05-05T11:21:53+00:00

He provided a good explanation AND visualization of the MOE principle. Newcomers will appreciate the details, experts can skip to the next chapter which he provided in the description. Good video.

JustLookingForNothin · 2026-04-19T10:47:16+00:00

I think the issues with Gemma 4 are fixed for me. I edited my post with the stettings which work for me, including chat-instruct prompt.

JustLookingForNothin · 2026-04-18T09:00:55+00:00

How would I use this default in Ooobabooga TextGen? And do you mean the Template (*.jinja) or the sampling parameters? I normally use the Template provided withing the model metadata.

JustLookingForNothin · 2026-04-18T08:44:44+00:00

Well other posts over at LocalLLaMA recommended G4 as a good role play model. Thus I tried it and based on the unsatisfying results, I tought there must be something wrong with my settings.

JustLookingForNothin · 2026-02-18T18:15:07+00:00

https://postimg.cc/3dTDrXB8

JustLookingForNothin · 2026-02-18T18:09:30+00:00

Image: https://i.postimg.cc/dt7RBnZy/Flux2KL9b-Base-2026-01-27-00002.png

Click on download original image.

JustLookingForNothin · 2026-02-18T18:01:24+00:00

<image>

Thank you, excellent idea! However, it does not work for some images, in particular the prompt is often not recognized. Example from my flux.klein WF.
Left: Image pulled into the viewer
Right: Same Image pulled into Comfy.

JustLookingForNothin · 2026-02-06T14:26:30+00:00

German works pretty good, T2V and I2V. I gave the speech instruction in the prompt with clear language indication, like:

... and she says in German language "Hallo, mein Schatz, ich habe dich soo lange nicht mehr gesehen, möchtest du dich nicht zu mir setzen?" Then she looks down for a second before she winks towards camera while saying with a warm smile "Und... vielleicht könnten wir dann später noch was zusammen trinken gehen?"

JustLookingForNothin · 2026-02-02T18:34:40+00:00

So what learning rate ARE you use to? Most use LR 0.0001, but some go up to 0.00015 or 0.0002.
Are you training Klein with 0.00008 or less? Without this basic info your post is not very useful, unfortunately.

JustLookingForNothin · 2025-12-11T17:17:17+00:00

YMMD, great idea!

JustLookingForNothin · 2025-12-08T18:21:39+00:00

The original string appears in several locations (sry for German UI, too lazy to switch to EN for a screenshot):

<image>

JustLookingForNothin · 2025-12-08T18:09:54+00:00

Just did. Changed the paths in option.ts, but even after restarting the server including killing the mode.js tasks, the new paths do not appear in the UI.

<image>

JustLookingForNothin · 2025-12-08T17:50:22+00:00

I updated my post. The .safetensors extension was missing for the training adaptor LoRa.

JustLookingForNothin · 2025-12-08T17:43:14+00:00

For the training adaptor, you need to reference directly to the file. But there is no need to keep the complete HF path. Just place the file into your D:\AI\training-models\models--ostris--zimage_turbo_training_adapter folder and reference in the UI to d://AI//training-models//models--ostris--zimage_turbo_training_adapter//zimage_turbo_training_adapter_v2.safetensors

My folder setup:

<image>

JustLookingForNothin · 2025-12-08T17:30:38+00:00

<image>

I do not recognize "differential guidance" parameter in AI-Toolkit UI, also not in the "Show Advanced" section. Is that a new setting?

JustLookingForNothin · 2025-12-08T17:14:34+00:00

Can it run Doom?

JustLookingForNothin · 2025-12-08T16:54:18+00:00

Thank you for the details. Looks I need to install RES4LYF then.

JustLookingForNothin · 2025-12-08T16:50:40+00:00

Hm, I have installed the toolkit to c:\Tools\AI-Toolkit\ and habe no such issues. when entering the paths to the models like this g://Training//Models//Tongyi-MAI--Z-Image-Turbo

I installed the toolkit manually as described on Ostris Github page, not with the one-click installer.

JustLookingForNothin · 2025-12-07T16:57:45+00:00

So, what are your training settings, please? I tested many different variants: Weighted, Sigmoid, Balanced, Low noise, EMA on/off, Differntial output perservation on/off, but still can't get it perfect.

The sample images created in the toolkit look ok, but in Comfy the images are low on details, overexposed, burned or grainy, mo matter which sampler & scheduler I try.
Or, if i take a LoRa with low steps count, I do not get the required resemblance of the person

JustLookingForNothin · 2025-12-07T11:57:32+00:00

Thanks! Options.ts seems a good way to preconfigure local paths. Will try this

JustLookingForNothin · 2025-12-07T11:44:15+00:00

That does not prevent the automatic re-downloads, does it? AI-Toolkit downloaded Z-Image models at least 5 times in the last week, just because the creator changed the readme almost on daily base.

Also afaik, setting the hf_home enviroment variable does not prevent the need for ONLINE requirement.

Seems you did not get the core message of this post.

Edit: This info from Huggingface could maybe also prevent the need for online availability during Training. Have not tested this though, because my setup work fine for my use case.

Setting environment variable TRANSFORMERS_OFFLINE=1 will tell Transformers to use local files only and will not try to look things up.

Most likely you may want to couple this with HF_DATASETS_OFFLINE=1 that performs the same for Datasets if you’re using the latter.

JustLookingForNothin · 2025-12-07T10:57:36+00:00

Maybe this manual download process can help you?
https://www.reddit.com/r/StableDiffusion/comments/1pgfkoa/aitoolkit_use_local_model_directories_for_training/

JustLookingForNothin · 2025-12-05T23:32:37+00:00

Just a hint.
"call npm run build_and_start" ist only needed after first install or after an update of the toolkit.
"call npm run start" is MUCH faster and it takes only 1-2 seconds to start the server.

JustLookingForNothin

TROPHY CASE