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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@@ -50,7 +50,7 @@ class SuperDiffPipeline(DiffusionPipeline, ConfigMixin):
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scheduler=scheduler.__class__.__name__,
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tokenizer=tokenizer.__class__.__name__,
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unet=unet.__class__.__name__,
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-
text_encoder=text_encoder.__class__.__name__
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device=device,
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batch_size=None,
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num_inference_steps=None,
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scheduler=scheduler.__class__.__name__,
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tokenizer=tokenizer.__class__.__name__,
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unet=unet.__class__.__name__,
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+
text_encoder=text_encoder.__class__.__name__,
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device=device,
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batch_size=None,
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num_inference_steps=None,
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