Instructions to use grisha2000/dreamstep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use grisha2000/dreamstep 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/dreamstep", 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:
- 86c29ffed1f57b9dbd353a1d0afc5dfb1ced18bd443a40c258b7fe4ef7659f73
- Size of remote file:
- 3.44 GB
- SHA256:
- 870d142d85b366926c85df50ececf7f989234d2c53f1bc949240f5be9f7caf2f
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