Text-to-Image
Diffusers
Trained with AutoTrain
stable-diffusion-xl
stable-diffusion-xl-diffusers
lora
template:sd-lora
Instructions to use kpal002/exactly-ai-diffusion-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kpal002/exactly-ai-diffusion-model with Diffusers:
pip install -U diffusers transformers accelerate
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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
End of training
Browse files
pytorch_lora_weights.safetensors
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pytorch_lora_weights_kohya.safetensors
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