<h2 id="trained-on-krea-2-turbo">Trained on Krea 2 Turbo</h2><h3 id="settings:">Settings:</h3>Steps: 20-24Upscaler: 4x UltraSharpScheduler: Basic or KarrasSampler: DDPM2CFG: 5-7Strengh: 0.5-0.8<h2 id="trained-on-flux.2-klein-4b">Trained on Flux.2 Klein 4B</h2><h3 id="settings:">Settings:</h3>Steps: 20-24Upscaler: 4x UltraSharpScheduler: KarrasSampler: DDIMCFG: 4Strengh: 0.5-0.6 <h3 id="example-prompts:">Example Prompts:</h3>Positive = &lt;johto&gt; 2d pokemon, single character, anime style picture, ray tracing, high resolution, ultra high quality, 4kNegative = blurry, noisy, grainy, realism (keep it simple)<h3 id="support-tensorvizion">Support TensorVizion</h3>Premium Workflows, Models &amp; Freebies:KoFI: <a target="_blank" rel="ugc" href="https://www.kofi.com/tensorvizion">https://www.kofi.com/tensorvizion</a>Patreon: <a target="_blank" rel="ugc" href="https://www.patreon.com/tensorvizion">https://www.patreon.com/tensorvizion</a>

BlazeJian

Trained on ZiTSupport:KoFI: <a target="_blank" rel="ugc" href="https://www.kofi.com/tensorvizion">https://www.kofi.com/tensorvizion</a>Patreon: <a target="_blank" rel="ugc" href="https://www.patreon.com/tensorvizion">https://www.patreon.com/tensorvizion</a>

BlazeJien-ZiT_c1-st5000.safetensors

Z-Image-Turbo

Flux.2-Klein-4B

Krea-2-Turbo


# 

## Model Introduction

This model is trained using the [Civision/model training](https://modelscope.ai/civision/modelTraining) environment and computing resources provided by ModelScope.

* Model Type: LoRA
* Base Model: [Tongyi-MAI/Z-Image-Turbo](https://modelscope.ai/models/Tongyi-MAI/Z-Image-Turbo)
* Training Code: [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)
* Data amount：43
* Total training steps：5000
* License: Apache-2.0

## Inference Code

Install [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio):

```bash
pip install diffsynth
```

Inference:

```python
from diffsynth.pipelines.z_image import ZImagePipeline, ModelConfig
import torch

pipe = ZImagePipeline.from_pretrained(
    torch_dtype=torch.bfloat16,
    device="cuda",
    model_configs=[
        ModelConfig(model_id="Tongyi-MAI/Z-Image-Turbo", origin_file_pattern="transformer/*.safetensors"),
        ModelConfig(model_id="Tongyi-MAI/Z-Image-Turbo", origin_file_pattern="text_encoder/*.safetensors"),
        ModelConfig(model_id="Tongyi-MAI/Z-Image-Turbo", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
    ],
    tokenizer_config=ModelConfig(model_id="Tongyi-MAI/Z-Image-Turbo", origin_file_pattern="tokenizer/"),
)
pipe.load_lora(pipe.dit, ModelConfig(model_id="tensorvizion/BlazeJien-ZiT", origin_file_pattern="BlazeJien-ZiT_c1-st5000.safetensors"))
prompt = "a cat"
image = pipe(prompt=prompt, num_inference_steps=8, cfg_scale=1)
image.save("image.jpg")
```


Files with SHA256: 18cdefad9d2727f3307a9c60f5b77d3d99a707f5046e092826f161b1f5be420c