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How to use Polycruz9/sketch-paint-lite 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-paint-lite")
prompt = "Sketch paint, An eye-level perspective, a medium-sized portrait of a woman, is depicted in a blue and white monochromatic fashion. The womans head is adorned with a large, fluffy, fuzzy hat, adorned with white flowers. Her hair is pulled back, framing her face, adding a touch of depth to the composition. She is wearing a black dress with a white scarf draped over her shoulders. Her dress is draped in a low-angle pattern, adding texture to the overall composition. The background is a dark blue, creating a stark contrast to the womans face."
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-paint-lite")
prompt = "Sketch paint, An eye-level perspective, a medium-sized portrait of a woman, is depicted in a blue and white monochromatic fashion. The womans head is adorned with a large, fluffy, fuzzy hat, adorned with white flowers. Her hair is pulled back, framing her face, adding a touch of depth to the composition. She is wearing a black dress with a white scarf draped over her shoulders. Her dress is draped in a low-angle pattern, adding texture to the overall composition. The background is a dark blue, creating a stark contrast to the womans face."
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 | 25 & 3070 |
| Epoch | 17 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 19
| 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-paint-lite"
trigger_word = "Sketch paint"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
You should use Sketch paint 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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