README.md

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: m00nl4nd1ng
widget:
  - text: astronaut hamster in the style of m00nl4nd1ng
    output:
      url: images/example_6adktoq5m.png
  - text: astronaut hamster in the style of m00nl4nd1ng
    output:
      url: images/example_x6tmtc1o5.png
  - text: astronaut hamster in the style of m00nl4nd1ng
    output:
      url: images/example_dqvgnsbs8.png
  - text: astronaut cat in the style of m00nl4nd1ng
    output:
      url: images/example_an1jkdgmn.png
  - text: astronaut cat in the style of m00nl4nd1ng
    output:
      url: images/example_bxaligavs.png
  - text: astronaut pig in the style of m00nl4nd1ng
    output:
      url: images/example_g8oqvjp4u.png
  - text: >-
      astronaut cat riding in a sparkling new 1956 BMW 507 in the style of
      m00nl4nd1ng
    output:
      url: images/example_x25mphdwx.png
  - text: >-
      astronaut hamster riding in a Pagani Zonda HP Barchetta on the Moon in the
      style of m00nl4nd1ng
    output:
      url: images/example_ci12lxbbe.png
  - text: >-
      Astronaut octopus operating a vintage space station control panel in the
      style of m00nl4nd1ng
    output:
      url: images/example_p1laue9cn.png

Flux Moonlanding76 Replicate

Trained on Replicate using:

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

Trigger words

You should use m00nl4nd1ng 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.float16).to('cuda')
pipeline.load_lora_weights('davidrd123/Flux-MoonLanding76-Replicate', 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