metadata

tags:
  - text-to-image
  - flux
  - lora
  - diffusers
  - template:sd-lora
  - ai-toolkit
widget:
  - text: >-
      a black t-shirt with a colorful design on it, hanging on a white wall. The
      design features a logo and text that reads "Let's Spread". TOK
    output:
      url: samples/1727305192656__000001000_0.jpg
  - text: >-
      in a bustling cafe, man wearing a black t-shirt with a colorful design on
      it, hanging on a white wall. The design features a logo and text that
      reads "Let's Spread". TOK
    output:
      url: samples/1727305218762__000001000_1.jpg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: TOK
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

blackraghanger1

Model trained with AI Toolkit by Ostris

Prompt
a black t-shirt with a colorful design on it, hanging on a white wall. The design features a logo and text that reads "Let's Spread". TOK

Prompt
in a bustling cafe, man wearing a black t-shirt with a colorful design on it, hanging on a white wall. The design features a logo and text that reads "Let's Spread". TOK

Trigger words

You should use TOK 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('histin116/blackraghanger1', weight_name='blackraghanger1.safetensors')
image = pipeline('a black t-shirt with a colorful design on it, hanging on a white wall. The design features a logo and text that reads "Let's Spread". TOK').images[0]
image.save("my_image.png")

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers