Instructions to use isatis/kw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use isatis/kw with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("isatis/kw", 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
change realistic to DPM++ 2M SDE Karras
Browse files- handler.py +5 -0
handler.py
CHANGED
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@@ -242,8 +242,13 @@ class EndpointHandler:
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# https://stablediffusionapi.com/docs/a1111schedulers/
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# DPM++ 2M Karras
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(
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pipe.scheduler.config,
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use_karras_sigmas=True,
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)
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# https://stablediffusionapi.com/docs/a1111schedulers/
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# DPM++ 2M Karras
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# pipe.scheduler = DPMSolverMultistepScheduler.from_config(
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# pipe.scheduler.config,
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# use_karras_sigmas=True,
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# )
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(
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pipe.scheduler.config,
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algorithm_type="sde-dpmsolver++",
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use_karras_sigmas=True,
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)
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