Instructions to use stablediffusionapi/dreamshaper-v8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/dreamshaper-v8 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/dreamshaper-v8", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- cc34f15832e26adb5bef6ae06d9981ff7fd00492134d8220f7d4478c92e0b042
- Size of remote file:
- 246 MB
- SHA256:
- e8581137737285d0f8981a8fc7563abb448eaa6f6a43f15c5dc880f0d21e0d02
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.