--- license: cc tags: - text-to-image - lora - diffusers - template:sd-lora base_model: - black-forest-labs/FLUX.1-dev widget: - text: collage, flowers, women, dresses, typography, colorful, abstract, chaotic, multimedia output: url: images/c1.png - text: collage, postcards, cities, travel, cut and paste output: url: images/c2.png - text: multimedia collage, detective, clue, 1940s, board game, ransom note output: url: images/c3.png - text: surreal collage, 2d mixed media, psychedelic, baroque, vibrant, dreamy, overgrown garden imagery, peacocks and pomegranates, vines and tendrils output: url: images/c4.png - text: collage, cottagecore, slice of life, cluttered, nature, multimedia output: url: images/c5.png - text: collage, typography, modern design, eye output: url: images/c6.png - text: 2008 film collage output: url: images/c7.png --- # collage art style lora for flux-dev no explicit trigger word, but you should include "collage", "multimedia collage", etc in your prompt. check the demo prompts for examples. works best at ~1.2 strength training data captions include: - `colorful collage, mixed images, watches, faces, text, vibrant, surreal` - `floral collage and train tracks, vintage piano, mixed media, surreal art, portrait elements` - `eclectic collage, vintage imagery, vibrant colors, pop art, surreal elements` also makes a very interesting cluttered-realism model when used on more normal prompts, eg `collage, dimly lit room, couch, TV, posters, clutter` since i do not own the data for this model, i can't really claim ownership of the model itself either. have fun! **run this with diffusers:** ```py import torch from diffusers import FluxPipeline import time import random # initialize pipeline and lora pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to("cuda") lora_weight = 1.2 pipe.load_lora_weights( 'bleepybloops/flux-collage-v1', adapter_name='collage_v1' ) pipe.set_adapters('collage_v1', adapter_weights=[lora_weight]) # set params and generate seed = -1 seed = seed if seed != -1 else random.randint(0, 2**32) print(seed) prompt = "multimedia collage, cut and paste, detective" out = pipe( prompt=prompt, guidance_scale=3.5, height=720, width=1024, num_inference_steps=25, generator=torch.Generator("cuda").manual_seed(seed), ).images[0] # save and display output filename=f"{time.time()}.png" out.save(filename) from IPython.display import Image, display display(Image(filename=filename)) ``` trained with https://github.com/ostris/ai-toolkit/blob/main/notebooks/FLUX_1_dev_LoRA_Training.ipynb