metadata

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
language:
  - en
tags:
  - flux
  - diffusers
  - lora
  - replicate
base_model: black-forest-labs/FLUX.1-dev
pipeline_tag: text-to-image
instance_prompt: MNALSA
widget:
  - text: >-
      a photo of MNALSA woman with a coffee in a parisian cafe, 50mm, sharp,
      award winning portrait photography
    output:
      url: >-
        https://replicate.delivery/yhqm/OQPHQ9kRw9ZpIBMub19XY8NxKznMDA50eSEjpx52QP3qoVrJA/out-0.webp
  - text: a photo of MNALSA woman with pink hair at a rave
    output:
      url: >-
        https://replicate.delivery/yhqm/apYK6kZFfZUYRyoJ11NzhHY2YXbrjCHajYIiN9EznGR4qVrJA/out-0.webp

Flux Mona Lisa

Prompt
a photo of MNALSA woman with a coffee in a parisian cafe, 50mm, sharp, award winning portrait photography

Prompt
a photo of MNALSA woman with pink hair at a rave

Run on Replicate:

https://replicate.com/fofr/flux-mona-lisa

Trained on Replicate using:

https://replicate.com/ostris/flux-dev-lora-trainer/train

Trigger words

You should use MNALSA to trigger the image generation.

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('fofr/flux-mona-lisa', weight_name='lora.safetensors')
image = pipeline('your prompt').images[0]

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