Instructions to use stablediffusionapi/dvarchmultipromptarchitecturetunedmodel-dvarchinterior with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/dvarchmultipromptarchitecturetunedmodel-dvarchinterior with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/dvarchmultipromptarchitecturetunedmodel-dvarchinterior", dtype=torch.bfloat16, device_map="cuda") prompt = "a girl wandering through the forest" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 7affd6e80902e1baa2f8694c01a769255f6437eb9b35694afa782fe90cb0f8a6
- Size of remote file:
- 246 MB
- SHA256:
- 0d22b3f5a858f21285f81b4277810f2716d5de98f84145bc58ac747a9dc38408
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.