Instructions to use stablediffusionapi/dkshi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/dkshi 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/dkshi", 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:
- 4e40cf1ef9b138c8977ce07ecd22f9362969bde1b9f0954400035e9c5a0f304d
- Size of remote file:
- 1.72 GB
- SHA256:
- 5cf793261b54000c2aa9d3e64b04b9712476d8099788477b44dc2ed948c34c90
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