Text-to-Image
Diffusers
StableDiffusionPipeline
stable-diffusion
sygil-diffusion
sygil-devs
finetune
stable-diffusion-1.5
Instructions to use Sygil/Sygil-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Sygil/Sygil-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Sygil/Sygil-Diffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "environment art, realistic" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit ·
d19ac48
1
Parent(s): 2fe9a79
Update README.md
Browse files
README.md
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@@ -57,7 +57,7 @@ pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
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pipe = pipe.to("cuda")
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prompt = "a
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image = pipe(prompt).images[0]
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image.save("astronaut_rides_horse.png")
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
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pipe = pipe.to("cuda")
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prompt = "a beautiful illustration of a fantasy forest"
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image = pipe(prompt).images[0]
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image.save("astronaut_rides_horse.png")
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