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
  - celebrity
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Jennifer Lawrence
widget:
  - text: ' '
    output:
      url: 29699987.jpeg
  - text: ' '
    output:
      url: 29699988.jpeg
  - text: ' '
    output:
      url: 29699992.jpeg
  - text: ' '
    output:
      url: 29699991.jpeg
  - text: ' '
    output:
      url: 29699989.jpeg

Jennifer Lawrence " Real Persons "

Model description

Jennifer Lawrence

Trigger words

You should use Jennifer Lawrence 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/jennifer-lawrence-real-persons', weight_name='jennifer-lawrence FLUX.safetensors')
image = pipeline('`Jennifer Lawrence `').images[0]

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