metadata

license: other
license_name: bespoke-lora-trained-license
license_link: >-
  https://multimodal.art/civitai-licenses?allowNoCredit=True&allowCommercialUse=Image&allowDerivatives=True&allowDifferentLicense=True
tags:
  - text-to-image
  - stable-diffusion
  - lora
  - diffusers
  - template:sd-lora
  - migrated
  - woman
  - actress
  - celeb
  - celebrity
  - heather graham
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: HeatherGrahamFlux
widget:
  - text: ' '
    output:
      url: 59671326.jpeg
  - text: ' '
    output:
      url: 59670044.jpeg
  - text: ' '
    output:
      url: 59670033.jpeg
  - text: ' '
    output:
      url: 59670034.jpeg
  - text: ' '
    output:
      url: 59670026.jpeg
  - text: ' '
    output:
      url: 59670029.jpeg
  - text: ' '
    output:
      url: 59670035.jpeg
  - text: ' '
    output:
      url: 59670037.jpeg
  - text: ' '
    output:
      url: 59670038.jpeg
  - text: ' '
    output:
      url: 59670039.jpeg
  - text: ' '
    output:
      url: 59670040.jpeg
  - text: ' '
    output:
      url: 59670042.jpeg
  - text: ' '
    output:
      url: 59670041.jpeg
  - text: ' '
    output:
      url: 59670045.jpeg
  - text: ' '
    output:
      url: 59670043.jpeg
  - text: ' '
    output:
      url: 59670047.jpeg
  - text: ' '
    output:
      url: 59670046.jpeg
  - text: ' '
    output:
      url: 59670049.jpeg
  - text: ' '
    output:
      url: 59670048.jpeg
  - text: ' '
    output:
      url: 59670050.jpeg

Heather Graham

Model description

Heather Joan Graham (born January 29, 1970) is an American actress. The accolades she has received include nominations for two Screen Actors Guild Awards, a Critics' Choice Movie Award, and an Independent Spirit Award.

Trigger words

You should use HeatherGrahamFlux to trigger the image generation.

Download model

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

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('Keltezaa/heather-graham', weight_name='HeatherGrahamFluxV1.safetensors')
image = pipeline('`HeatherGrahamFlux`').images[0]

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