Instructions to use YiYiXu/modular-diffdiff-0704 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YiYiXu/modular-diffdiff-0704 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YiYiXu/modular-diffdiff-0704", 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
Update block.py
Browse files
block.py
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@@ -167,10 +167,6 @@ class SDXLDiffDiffDenoiseLoopBeforeDenoiser(PipelineBlock):
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@property
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def intermediates_outputs(self) -> List[OutputParam]:
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return [OutputParam("latents", type_hint=torch.Tensor, description="The denoised latents")]
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@property
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def expected_components(self) -> List[ComponentSpec]:
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return [
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]
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@property
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def expected_components(self) -> List[ComponentSpec]:
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return [
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