Instructions to use Disty0/sote-diffusion-cascade-decoder_pre-alpha0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Disty0/sote-diffusion-cascade-decoder_pre-alpha0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Disty0/sote-diffusion-cascade-decoder_pre-alpha0", 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 README.md
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README.md
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@@ -23,8 +23,8 @@ from diffusers import StableCascadeDecoderPipeline, StableCascadePriorPipeline
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prompt = "(extremely aesthetic, best quality, newest), 1girl, solo, cat ears, looking at viewer, blush, light smile, upper body,"
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negative_prompt = "very displeasing, worst quality, monochrome, sketch, blurry, fat, child,"
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prior = StableCascadePriorPipeline.from_pretrained("Disty0
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decoder = StableCascadeDecoderPipeline.from_pretrained("SoteDiffusion-Cascade_Decoder", torch_dtype=torch.float16)
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prior.enable_model_cpu_offload()
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prior_output = prior(
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prompt = "(extremely aesthetic, best quality, newest), 1girl, solo, cat ears, looking at viewer, blush, light smile, upper body,"
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negative_prompt = "very displeasing, worst quality, monochrome, sketch, blurry, fat, child,"
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prior = StableCascadePriorPipeline.from_pretrained("Disty0/SoteDiffusion-Cascade_pre-alpha0", torch_dtype=torch.float16)
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decoder = StableCascadeDecoderPipeline.from_pretrained("Disty0/SoteDiffusion-Cascade_Decoder", torch_dtype=torch.float16)
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prior.enable_model_cpu_offload()
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prior_output = prior(
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