Downloads · 30 days
53
11% of all-time downloads
lyraaaa/flux-collage-v1
flux-collage-v1 is a text-to-image model from lyraaaa. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as cc.
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
Downloads · 30 days
53
11% of all-time downloads
All-time downloads
481
Public
Repo size
65 MB
Likes
1
Public
Click a slice to open those files.
.safetensors51.7 MB · 81%
From the Hugging Face model README
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, surrealfloral collage and train tracks, vintage piano, mixed media, surreal art, portrait elementseclectic collage, vintage imagery, vibrant colors, pop art, surreal elementsalso 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:
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