| --- |
| base_model: Tongyi-MAI/Z-Image-Turbo |
| tags: |
| - lora |
| - text-to-image |
| - z-image-turbo |
| - style |
| - diffusion |
| license: other |
| --- |
| |
| # a-cold-wall — LoRA |
|
|
| A LoRA adapter trained for the concept/style **"a-cold-wall"**. |
|
|
| ## Trigger word |
| Use this token in your prompt: |
| - **`a-cold-wall`** |
|
|
| ## Base model |
| - **Tongyi-MAI/Z-Image-Turbo** |
|
|
| ## Files |
| - `a-cold-wall.safetensors` — the LoRA weights |
| - `config.yaml`, `job_config.json` — training configuration (for reproducibility) |
|
|
| ## How to use |
|
|
| ### A) ComfyUI / AUTOMATIC1111 |
| 1. Put `a-cold-wall.safetensors` into your LoRA folder. |
| 2. Use it in your prompt, e.g.: |
| - `a-cold-wall, fashion outfits, editorial photo, high detail` |
|
|
| (Adjust LoRA strength to taste, e.g. 0.6–1.0.) |
|
|
| ### B) Diffusers (generic example) |
| > Depending on your setup, you may need to use the correct pipeline class for Z-Image-Turbo. |
|
|
| ```python |
| import torch |
| from diffusers import DiffusionPipeline |
| |
| pipe = DiffusionPipeline.from_pretrained( |
| "Tongyi-MAI/Z-Image-Turbo", |
| torch_dtype=torch.bfloat16 |
| ).to("cuda") |
| |
| pipe.load_lora_weights("thorjank/a-cold-wall-lora", weight_name="a-cold-wall.safetensors") |
| |
| prompt = "a-cold-wall, fashion outfits, editorial photo, high detail" |
| image = pipe(prompt).images[0] |
| image.save("out.png") |