Instructions to use Datou1111/Slow-Shutter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Datou1111/Slow-Shutter with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Datou1111/Slow-Shutter") prompt = "slow shutter photography motion blur, A captivating portrait of a young woman with short, blond hair and bangs. She wears a white button-down shirt, her expression serene. The background is a blur of motion, streaks of red and yellow light suggesting a bustling cityscape at night. A red car speeds past, its form elongated by the camera's long exposure. The overall effect is dynamic and dreamlike, capturing a sense of fleeting beauty amidst the rush of urban life. Use a painterly style, emphasizing the contrast between the sharp focus of the woman and the blurred background." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Publish Dataset?
#1
by SantiagoJN - opened
Hi!
Nice results! I was wondering if there are any plans to publish the dataset on which this LoRA was trained?
Thanks!