Instructions to use haopt/scflow_t2i with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use haopt/scflow_t2i with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("haopt/scflow_t2i", 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
- Xet hash:
- 4b1240dc8096bbccacdedd061c00b9a24d1f76bce98a4faf85fed9c3b0bac5ab
- Size of remote file:
- 1 kB
- SHA256:
- 41d4e8b5b77f1d05bc37e64757554209c00feda2e53a784724aff2cd79f0b32b
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