Instructions to use tdvipp/dreambooth-lora-diffuser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tdvipp/dreambooth-lora-diffuser with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("tdvipp/dreambooth-lora-diffuser") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- be14ef14a2be7e2b14f7f7b2efd6f5e15e82065d651a4132a4e2887e411e7479
- Size of remote file:
- 6.59 MB
- SHA256:
- 919a4757a1903b9727cbfc085c82ebd66ff52da74e3c02eeda78c39787072fc3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.