Text-to-Image
Diffusers
StableDiffusionPipeline
stablediffusionapi.com
stable-diffusion-api
ultra-realistic
Instructions to use stablediffusionapi/dreamshapern with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/dreamshapern 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/dreamshapern", 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:
- 1ec52eaebbbf96b9e962d37a4b152b40fcdb7f998c8bfa0e89c04933f9b4a97f
- Size of remote file:
- 167 MB
- SHA256:
- 9cb2825c95e060f6cf84d17b1c46058255bdc315ee25644b09b028ef861023d9
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