Instructions to use hakurei/artstation-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hakurei/artstation-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("hakurei/artstation-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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Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.f6d1675
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Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (#5)
- Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (16d5a248500dea1d5e976600a68fc1284f3a5e99)0686c53
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Add `clip_sample=False` to scheduler to make model compatible with DDIM. (#3)
- Add `clip_sample=False` to scheduler to make model compatible with DDIM. (70b7ed812201f514151c413be73851346c488892) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>51b5fd7
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Update README.md
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Update model card
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Add weights
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initial commit
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