Instructions to use BiliSakura/ADM-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/ADM-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BiliSakura/ADM-diffusers", 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
Delete model_index.json
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model_index.json
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{
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"_class_name": "ADMPipeline",
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"_diffusers_version": "0.36.0",
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"scheduler": [
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"scheduling_adm",
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"ADMScheduler"
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],
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"unet": [
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"unet_adm",
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"ADMUNet2DModel"
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],
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"classifier": [
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"classifier_adm",
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"ADMClassifierModel"
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]
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}
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