Instructions to use superdiff/superdiff-sd-v1-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use superdiff/superdiff-sd-v1-4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("superdiff/superdiff-sd-v1-4", 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
- Draw Things
- DiffusionBee
Update pipeline.py
Browse files- pipeline.py +1 -1
pipeline.py
CHANGED
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@@ -43,7 +43,7 @@ class SuperDiffPipeline(DiffusionPipeline, ConfigMixin):
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#self.scheduler = scheduler
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device = "cuda" if torch.cuda.is_available() else "cpu"
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-
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vae.to(device)
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unet.to(device)
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text_encoder.to(device)
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#self.scheduler = scheduler
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device = "cuda" if torch.cuda.is_available() else "cpu"
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+
print("hello this is a test", flush=True)
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vae.to(device)
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unet.to(device)
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text_encoder.to(device)
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