---
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))

```

<Gallery />

trained with https://github.com/ostris/ai-toolkit/blob/main/notebooks/FLUX_1_dev_LoRA_Training.ipynb