Instructions to use grisha2000/dreamgrisha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use grisha2000/dreamgrisha with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("grisha2000/dreamgrisha", 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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- e3188a6618ed450410e61250aa028939c6a011594fcc987c0c64d94fdad689f2
- Size of remote file:
- 246 MB
- SHA256:
- 7eeb4e5abd9d0736be4b3ef9cedf39d002144f958d03eede836e79b5e4cbc6dc
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