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Watercolor Sketch Style - FLUX

Prompt
wat3rc0l0r, a robot holding a sign that says "I LOVE TOASTERS!"
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young woman in a greenhouse, tending to plants, peaceful, wat3rc0l0r
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wat3rc0l0r, an old man annoyed, looking at the camera
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bohemian painter, laurel wreath, sunset painting session, wat3rc0l0r
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wat3rc0l0r, a couple walking on a dirt road with butterflies in the air
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woman in art studio, canvas, paint-splattered apron, wat3rc0l0r
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lady pirate, tricorn hat, wind-blown hair, defiant grin, wat3rc0l0r
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p0p_r0y, wat3rc0l0r, a pop-art painting of a 50's rocker cat holding a sign that says "(Cool Cats Use SwarmUI:1.4)" (halftones:1.5)
Prompt
tshirt design, my little pony, the style of wat3rc0l0r
Prompt
tshirt design, my little pony, the style of wat3rc0l0r

Model description

Trigger word is wat3rc0l0r but I have had good results without the trigger word.. I like to run this at 1.0 but you can lower it to lessen the effect or raise it to 1.3 to really get some unique images. Let me know your thoughts on this lora. I worked really hard and many hours training it with different methods to give you the best lora I possibly could. If you have an idea for a lora shot me a message!

I use SwarmUI for 95% of my image generations and encourage you to try it out! Here's the link to the GitHub repo and also checkout this install video from Kleebz Tech AI to get you started!

Trigger words

You should use wat3rc0l0r to trigger the image generation.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

Use it with the 🧨 diffusers library

from diffusers import AutoPipelineForText2Image
import torch

device = "cuda" if torch.cuda.is_available() else "cpu"

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to(device)
pipeline.load_lora_weights('SouthbayJay/watercolor-sketch-style-flux', weight_name='watercolor_Flux_v3.safetensors')
image = pipeline('tshirt design, my little pony, the style of wat3rc0l0r').images[0]

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers

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