import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("Raul2718/CFD-FLUX.1-dev-LoRA")
prompt = "-"
image = pipe(prompt).images[0]CFD FLUX.1 [dev] LoRA
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Model description
LoRA (rank=16) adapter for FLUX.1 [dev] model trained on Chicago Face Database.
Please cite Chicago Face Database if you use this LoRA:
@article{cfd_1, author = {Ma, Debbie S. and Correll, Joshua and Wittenbrink, Bernd}, title = {The Chicago Face Database: A Free Stimulus Set of Faces and Norming Data}, journal = {Behavior Research Methods}, year = {2015}, volume = {47}, pages = {1122--1135}, doi = {10.3758/s13428-014-0532-5} }
@article{cfd_2, author = {Ma, Debbie S. and Kantner, Justin and Wittenbrink, Bernd}, title = {Chicago Face Database: Multiracial Expansion}, journal = {Behavior Research Methods}, year = {2020}, doi = {10.3758/s13428-020-01482-5} }
@article{cfd_3, author = {Lakshmi, B. and Wittenbrink, Bernd and Correll, Joshua and Ma, Debbie S.}, title = {The India Face Set: International and Cultural Boundaries Impact Face Impressions and Perceptions of Category Membership}, journal = {Frontiers in Psychology}, volume = {12}, pages = {161}, year = {2020}, doi = {10.3389/fpsyg.2021.627678} }
Trigger words
You should use s7ll2f4h to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Base model
black-forest-labs/FLUX.1-dev