Update README.md

README.md

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----
-license: mit
----
+---
+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")