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How to use Polycruz9/sketch-smudged with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("Polycruz9/sketch-smudged")
prompt = "Sketch Smudge, A gray and white drawing of a womans head is depicted on a white canvas background. The womans face is facing the left side of the frame, her eyes are open and her lips are slightly parted. Her hair is long and cascades over her shoulders. She is wearing a gray knitted cap, and a white scarf around her neck. The background is a vibrant red, and the womans neck is adorned with a white design."
image = pipe(prompt).images[0]pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("Polycruz9/sketch-smudged")
prompt = "Sketch Smudge, A gray and white drawing of a womans head is depicted on a white canvas background. The womans face is facing the left side of the frame, her eyes are open and her lips are slightly parted. Her hair is long and cascades over her shoulders. She is wearing a gray knitted cap, and a white scarf around her neck. The background is a vibrant red, and the womans neck is adorned with a white design."
image = pipe(prompt).images[0]
______ ______ __ __ __ ______ ______ __ __ ______ __ ______
/\ == \/\ __ \ /\ \ /\ \_\ \ /\ ___\ /\ == \ /\ \/\ \ /\___ \ /\ \ /\ __ \
\ \ _-/\ \ \/\ \\ \ \____\ \____ \\ \ \____\ \ __< \ \ \_\ \\/_/ /__ \ \ \\ \ \/\ \
\ \_\ \ \_____\\ \_____\\/\_____\\ \_____\\ \_\ \_\\ \_____\ /\_____\ \ \_\\ \_____\
\/_/ \/_____/ \/_____/ \/_____/ \/_____/ \/_/ /_/ \/_____/ \/_____/ \/_/ \/_____/









Image Processing Parameters
| Parameter | Value | Parameter | Value |
|---|---|---|---|
| LR Scheduler | constant | Noise Offset | 0.03 |
| Optimizer | AdamW | Multires Noise Discount | 0.1 |
| Network Dim | 64 | Multires Noise Iterations | 10 |
| Network Alpha | 32 | Repeat & Steps | 22 & 3290 |
| Epoch | 18 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 26 [ 14 bit raw ]
| Dimensions | Aspect Ratio | Recommendation |
|---|---|---|
| 1280 x 832 | 3:2 | Best |
| 1024 x 1024 | 1:1 | Default |
import torch
from pipelines import DiffusionPipeline
base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "Polycruz9/sketch-smudged"
trigger_word = "Sketch Smudge"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
You should use Sketch Smudge to trigger the image generation.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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