Instructions to use nitrosocke/Arcane-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/Arcane-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("nitrosocke/Arcane-Diffusion", 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 Settings
- Draw Things
- DiffusionBee
Commit History
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add gradio demo and colab link
added a link to gradio demo for fine-tuned SD models and colab link051781c
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Add Arcane Diffusion for Diffusers (#11)
- add diffusers weights (3c52108e99834093febedf88561cba85d99d6e75) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>ee738ff
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deleted the model_index file
deleted the model_index file in order to preparing the upload of the diffusers6dc4a49 -
Add model_index.json for compatibility with Diffusion Pipeline (#7)
- Add model_index.json for compatibility with Diffusion Pipeline (20f6f9c0547e5bd1de2683b7b38f5a2b217e3e91) Co-authored-by: AQ <anzorq@users.noreply.huggingface.co>da4c8ed
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Update README.md
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uploaded new sample images
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uploaded v3 of arcane-diffusion
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Uploaded the new version of arcane-diffusion
This model was trained using the dreambooth diffusers method and ckpt conversion script.8c6e5a5
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Upload arcane-diffusion-output-images.jpg
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Upload arcane-diffusion-training-images.jpg
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Uploaded ckpt file for arcane diffusion
Arcane Diffusion Model by Nitrosocke 5k steps trained on screenshots of the arcane tv show3db2328 -
initial commit
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