Instructions to use d-wang26/mk1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use d-wang26/mk1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("d-wang26/mk1", 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
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Download diffusers/docs/source/en/api/normalization.md from d-wang26/mk1: direct link, hf CLI and curl.
- Browser
- Download file 969 Bytes
-
https://huggingface.co/d-wang26/mk1/resolve/main/diffusers/docs/source/en/api/normalization.md
- Command line
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hf download hf://d-wang26/mk1/diffusers/docs/source/en/api/normalization.md
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curl -L -o normalization.md https://huggingface.co/d-wang26/mk1/resolve/main/diffusers/docs/source/en/api/normalization.md
969 Bytes
Normalization layers
Customized normalization layers for supporting various models in 🤗 Diffusers.
AdaLayerNorm
[[autodoc]] models.normalization.AdaLayerNorm
AdaLayerNormZero
[[autodoc]] models.normalization.AdaLayerNormZero
AdaLayerNormSingle
[[autodoc]] models.normalization.AdaLayerNormSingle
AdaGroupNorm
[[autodoc]] models.normalization.AdaGroupNorm