| --- |
| base_model: Tongyi-MAI/Z-Image-Turbo |
| tags: |
| - lora |
| - text-to-image |
| - diffusion |
| - z-image-turbo |
| license: other |
| --- |
| |
| # sofia-russo — LoRA (Z-Image-Turbo) |
|
|
| LoRA adapter trained for the concept/style **"sofia-russo"**. |
|
|
| ## Trigger word |
| Use this token in your prompt: |
| - **`sofia-russo`** |
|
|
| > Note: Some workflows/tokenizers may also respond to `sofia russo` (with a space). If the trigger doesn’t “bite”, try both variants. |
|
|
| ## Base model |
| - **Tongyi-MAI/Z-Image-Turbo** |
|
|
| ## Files |
| - `*.safetensors` — LoRA weights |
| - `config.yaml`, `job_config.json` — training configuration |
| - (optional) `log.txt` — training log |
|
|
| ## How to use |
|
|
| ### A) ComfyUI / AUTOMATIC1111 |
| 1. Put the `.safetensors` file into your LoRA folder. |
| 2. Prompt example: |
| - `sofia-russo, outdoor golden hour portrait, natural warm sunlight, high detail` |
|
|
| (Adjust LoRA strength to taste, e.g. 0.6–1.0.) |
|
|
| ### B) Diffusers (generic example) |
| ```python |
| import torch |
| from diffusers import DiffusionPipeline |
| |
| pipe = DiffusionPipeline.from_pretrained( |
| "Tongyi-MAI/Z-Image-Turbo", |
| torch_dtype=torch.bfloat16 |
| ).to("cuda") |
| |
| # Replace with your actual filename: |
| pipe.load_lora_weights("thorjank/<REPO_NAME>", weight_name="<YOUR_LORA_FILENAME>.safetensors") |
| |
| prompt = "sofia-russo, outdoor golden hour portrait, natural warm sunlight, high detail" |
| image = pipe(prompt).images[0] |
| image.save("out.png") |