Text-to-Image
Diffusers
diffusers-training
lora
template:sd-lora
stable-diffusion-xl
stable-diffusion-xl-diffusers
Instructions to use Tonioesparza/ourhood_training_dreambooth_lora_2_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Tonioesparza/ourhood_training_dreambooth_lora_2_0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SG161222/RealVisXL_V5.0", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Tonioesparza/ourhood_training_dreambooth_lora_2_0") prompt = "A photograph, of an Ourhood privacy booth, front view, in a warehouse eventspace environment, in the style of event photography, silken oak frame, checkered warm grey exterior fabric, checkered warm grey interior fabric, curtains, diner seating, pillows" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 3a66a70646b115b3df989cdb859ae6f988830cb58be64c3eab733efcc8f31db4
- Size of remote file:
- 988 Bytes
- SHA256:
- 384aaf346029be094d1ffd6adc716843b43c608f4b7d33a244ce4cda6859aa3d
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