Text-to-Image
Diffusers
Trained with AutoTrain
stable-diffusion
stable-diffusion-diffusers
lora
template:sd-lora
Instructions to use bayndrysf/dreambooth-project-style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bayndrysf/dreambooth-project-style 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-2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("bayndrysf/dreambooth-project-style") prompt = "Istanbul photos from Ara Guler who is a photographer" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("bayndrysf/dreambooth-project-style")
prompt = "Istanbul photos from Ara Guler who is a photographer"
image = pipe(prompt).images[0]AutoTrain LoRA DreamBooth - bayndrysf/dreambooth-project-style
These are LoRA adaption weights for stabilityai/stable-diffusion-2. The weights were trained on Istanbul photos from Ara Guler who is a photographer using DreamBooth. LoRA for the text encoder was enabled: True.
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Base model
stabilityai/stable-diffusion-2