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-schnell
pipeline_tag: text-to-image
instance_prompt: TTLDRMCHR
inference:
parameters:
width: 512
height: 1024
widget:
- text: >-
geometric tall character design on white background, in the style of
TTLDRMCHR. Superman
example_title: Superman
output:
url: samples/superman.png
- text: >-
geometric tall character design on white background, in the style of
TTLDRMCHR. Wonder woman
example_title: Wonder Woman
output:
url: samples/wonder-woman.png
- text: geometric tall character design, in the style of TTLDRMCHR. Donald Trump
example_title: Donald Trump
output:
url: samples/donald-trump.png
- text: geometric tall character design, in the style of TTLDRMCHR. Hulk
example_title: Hulk
output:
url: samples/hulk.png
- text: >-
geometric tall character design, in the style of TTLDRMCHR. c-3po from
starwars
example_title: C-3PO
output:
url: samples/c3po.png
- text: >-
TTLDRMCHR cartoon portrait of a mexican skeleton playing the guitar. Dark
wooden background. neon lights
example_title: Día de los Muertos
output:
url: samples/mexican-skelleton.png
- text: >-
geometric tall character design, in the style of TTLDRMCHR. A strange man
with the face of a fish.
example_title: Fishman
output:
url: samples/fish-man.png
Flux Lora Total Drama Character White Bg
Trigger words
You should use TTLDRMCHR
to trigger the image generation.
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
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('lichorosario/flux-lora-total-drama-character-white-bg', 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