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: TOK
widget:
- text: satellite view of a small city, american suburb, in the style of TOK
output:
url: images/example_6q1cifoc2.png
- text: satellite view of a small city, eastern europe, in the style of TOK
output:
url: images/example_5onx2x69s.png
Flux Satellite

- Prompt
- satellite view of a small city, american suburb, in the style of TOK

- Prompt
- satellite view of a small city, eastern europe, in the style of TOK
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
Trigger words
You should use TOK
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('jbilcke-hf/flux-satellite', 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