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: KUJI
widget:
- text: Cherry tree in the style of KUJI
output:
url: examples/1.JPG
- text: Vibrant sunset. Effects and flares in the style of KUJI.
output:
url: examples/2.JPEG
- text: >-
View through car window looking out on the desert, light leak effect,
scenery, blurry, flmft in the style of KUJI.
output:
url: examples/3.JPG
- text: >-
A mountain peak piercing through a sea of clouds at sunrise, with
alpenglow on the summits, lens flare streaking across, flmft in the style
of KUJI
output:
url: examples/4.JPG
- text: Sunny day at the beach in the style of KUJI.
output:
url: examples/5.WEBP
- text: >-
Teenage bedroom with posters and clutter, warm color palette, flmft in the
style of KUJI.
output:
url: examples/6.JPG
- text: Mount fuji landscape in the style of KUJI.
output:
url: examples/7.JPG
- text: >-
A pier extending into a calm ocean, reflected in the water, with a sky
full of cotton candy cirrocumulus clouds at sunset, dreamy double exposure
effect, flmft in the style of KUJI
output:
url: examples/8.JPG
- text: >-
A lone tree on a hilltop, framed by a sky with layered lenticular clouds
catching the last light of day, vignette effect, flmft in the style of
KUJI
output:
url: examples/9.JPG
Flux Lora Kuji
A Huji cam inspired lora finetuning of flux-koda. Works best with landscapes and naturalistic environments. In order to obtain better results, combine the keywords 'flmft' and 'in the style of KUJI'. More examples in this drive folder.
Fun fact: training set was mostly made by images taken by me 🤗.
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
Trigger words
Combine the keywords 'flmft' and 'in the style of KUJI'
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('ludocomito/flux-lora-kuji', 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