z-tao / README.md
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---
tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- ai-toolkit
widget:
- text: A person in a korean rich hotel Z.TAO, pink-purple hair color, white suit
best quality, real photo, 26K, Jungkook earrings
output:
url: samples/1732790138571__000001551_0.jpg
- text: A person in a thai cafe Z.TAO with rainbow hair color, yellow suit best
quality, real photo, 26K, Jungkook hairstyle
output:
url: samples/1732790168442__000001551_1.jpg
- text: A person in a russian forest Z.TAO with dark grey hair color, red-orange
suit, best quality, real photo, 26K, high details, happy face
output:
url: samples/1732790198346__000001551_2.jpg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Z.TAO
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
---
# z-tao
<Gallery />
## Trigger words
You should use `Z.TAO` to trigger the image generation.
## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
[Download](/openfree/z-tao/tree/main) them in the Files & versions tab.
## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
```py
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('openfree/z-tao', weight_name='z-tao.safetensors')
image = pipeline('A person in a korean rich hotel Z.TAO, pink-purple hair color, white suit best quality, real photo, 26K, Jungkook earrings').images[0]
image.save("my_image.png")
```
For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)