import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("kpal002/exactly-ai-diffusion-model")
prompt = "Create vibrant and colorful portraits with exaggerated, bold brushstrokes that capture the emotional essence and character of the subjects. Focus on close-up shots of faces, highlighting large, expressive eyes and detailed facial features. Use a dynamic and vivid color palette to convey intense emotions and a dreamlike quality, enhancing the abstract realism and emotional expressionism in each portrait."
image = pipe(prompt).images[0]AutoTrain SDXL LoRA DreamBooth - kpal002/exactly-ai-diffusion-model
Model description
These are kpal002/exactly-ai-diffusion-model LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: False.
Special VAE used for training: None.
Trigger words
You should use Create vibrant and colorful portraits with exaggerated, bold brushstrokes that capture the emotional essence and character of the subjects. Focus on close-up shots of faces, highlighting large, expressive eyes and detailed facial features. Use a dynamic and vivid color palette to convey intense emotions and a dreamlike quality, enhancing the abstract realism and emotional expressionism in each portrait. to trigger the image generation.
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Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Base model
stabilityai/stable-diffusion-xl-base-1.0