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:
- abf90e5b893848e98269d88fa8fcaaf53b224db6d9fcbf76ac44d800c3f74dac
- Size of remote file:
- 1.01 kB
- SHA256:
- 4673c23bd58c25799c051455f20553d9cd35cdc07abc114a714d200ef960b42a
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