New Mecha style for Z-Image-Turbo V2!

This time, i did a training using Z-Image De-Turbo, an undistilled version of ZIT. I also raised the LR to 0.0002 and made a 64 dim LoRA before reducing the rank to 32 and carefully merge it with the previous LoRA. I also removed the trigger word, the only constant remaining is the fact that it was training on "Digital illustrations" with an "anime-like" "semi-realistic style".

This helped me achieve better results even if i raise the CFG to 1.2 (distilled models don't have a CFG and should be used with CFG = 1, aka no negative prompt).

All showcase pictures are made with 9 steps, CFG 1.2, Euler/Beta (aka Smoothstep in stable-diffusion.cpp) using the Q4_K quant, the ablitered version of Qwen3-4B for the TE and the regular VAE, plus a flow shift at 3. They got an img2img pass at 0.5 denoise with the same parameters to smooth some details.

Below a part of my ugly python wrapper script to parse multiple prompt ;-)

Enjoy! 💜

New Mecha style for Flux.2 Klein 4B!

This is a very first attempt at training a LoRA for Flux.2 Klein 4B! It was done using ai-toolkit using the 4B-Base version, but all pictures are generated using the distilled version here.

All showcase pictures are done using the Q4_K quantized version and stable-diffusion.cpp, first by doing a txt2img and then a img2img to sharpen the result a bit.

This is a very first test and i still prefer ZIT, but the img edit capabilities are interesting and i wanted to have a version of the model that new my style (i'll probably try to train a better version later).

Here is demo of the img edit. The source image was made using ZIT and my LoRA:

And with this prompt and even a different resolution of 832x1216,

Change the girl top from red to green and her hair from blonde to orange <lora:new_mecha_klein4b:0.8>

I got this picture 😁 (ok, it's a very basic test, but i'll try more stuff and at least, i am happy this run locally on my GTX 1060):

New Mecha style for Z-Image-Turbo!

This is a one shot test to allow me (and everyone of course) to test ZIT stuff with New Mecha style. Works best with 8-10 steps.

Trigger: Start your prompt with "NewMecha style illustration." followed by something (this can be altered) like "This is a highly detailed, digital illustration of a...". You can add "anime-like" if you wish for a flatter look or "CGI" if you want more 3D.

This LoRA was trained using ai-toolkit default config (since the on-site training is failing hard on ZIT) and a dataset of 250 pictures generated using New Mecha and captionned using JoyCaption.

Since this is a dataset of Illustrious pictures, the overall result is a bit under what ZIT supposedly can render, but lowering the LoRA weight and adding more stuff is the goal (that's why on-site i put 0.8 as the max weight).

The showcase was done by captionning my usual showcase pictures using JoyCaption too and the ugliest Gradio + Diffusers app ever (to avoid paying Yellow Buzz):

import gradio as gr
import torch
from diffusers import ZImagePipeline
from uuid import uuid4
from PIL.PngImagePlugin import PngInfo
from datetime import datetime, timezone

device = "cuda"
dtype = torch.bfloat16

pipe = ZImagePipeline.from_pretrained(
    "Tongyi-MAI/Z-Image-Turbo",
    dtype=dtype,
).to(device)

pipe.load_lora_weights(
    "./output/new_mecha_zit",
    weight_name="new_mecha_zit_000002750.safetensors",
    adapter_name="new_mecha",
)

pipe.set_adapters(["new_mecha"], adapter_weights=[0.8])


def generate(prompt, seed, steps):
    generator = torch.Generator(device).manual_seed(seed)

    image = pipe(
        prompt=f"NewMecha style illustration. {prompt}",
        num_inference_steps=steps,
        guidance_scale=1,
        width=832,
        height=1216,
        generator=generator,
    ).images[0]

    im_path = f"./im-outputs/{uuid4()}.png"

    metadata = PngInfo()

    timestamp = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%S.%fZ")

    ressources = 'Civitai resources: [{"type":"checkpoint","modelVersionId":2442439,"modelName":"Z Image","modelVersionName":"Turbo"},{"type":"lora","weight":0.8,"modelVersionId":2507250,"modelName":"(ZIT) New Mecha style","modelVersionName":"v1.0"}], Civitai metadata: {}'

    metadata.add_text(
        "parameters",
        f"NewMecha style illustration. {prompt}\nNegative prompt: \nSteps: {steps}, Sampler: Undefined, CFG scale: 1, Seed: {seed}, Size: 832x1216, Clip skip: 2, Created Date: {timestamp}, {ressources}",
    )

    image.save(im_path, pnginfo=metadata)

    return im_path


demo = gr.Interface(
    fn=generate,
    inputs=[
        gr.Textbox(
            label="prompt",
            value="This is a highly detailed, digital anime-style illustration of a young woman in a black dress.",
            lines=6,
        ),
        gr.Number(label="seed", value=42, minimum=1, precision=0),
        gr.Number(label="steps", value=8, minimum=1, precision=0),
    ],
    outputs=[gr.Image(height=608)],
    flagging_mode="never",
    clear_btn=None,
)

demo.launch(server_name="0.0.0.0", server_port=8000)

Enjoy and please give me any feedback you feel like regarding this LoRA (that's probably the only one i'll make for ZIT, at least until i can generate locally instead of on a costly GPU instance).