Instructions to use IsaacAkintaro/household_diffusion_tutorial_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use IsaacAkintaro/household_diffusion_tutorial_output with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("IsaacAkintaro/household_diffusion_tutorial_output", torch_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:
- 2de071df1d6de7f8878e1070e6a98be69ca7af3c112002f1fcf8c9849e037945
- Size of remote file:
- 455 MB
- SHA256:
- 8faa02fa4a50d3aa1757d1e1ae5b6fd75f71f7f24a0cc181622d80df270242d8
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