metadata

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

Prompt
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

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 them in the Files & versions tab.

Use it with the 🧨 diffusers library

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