Instructions to use ringhyacinth/nail-set-diffuser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ringhyacinth/nail-set-diffuser with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ringhyacinth/nail-set-diffuser", 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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Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (#4)
- Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (c95d06c8670dbb76748dcf25db88e8d27488d787)a57d1ec
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Add `scale_factor` to vae config. (#3)
- Add `scale_factor` to vae config. (135ad1e29ef2a6d322a3ff2bee9fb4765d1a78d9) Co-authored-by: Suraj Patil <valhalla@users.noreply.huggingface.co>7f7c9c9
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Add `clip_sample=False` to scheduler to make model compatible with DDIM. (#2)
- Add `clip_sample=False` to scheduler to make model compatible with DDIM. (2fe4f0b423b0d2b8a818704e04094b9c60124fa0) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>a72069a
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Correct `sample_size` of Stable Diffusion 1's unet to have correct width and height default (#1)
- Correct `sample_size` of Stable Diffusion 1's unet to have correct width and height default (60f94e2bfd47ea6bb4fce80ea2b5a39f5e8d53a3) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>6d9c1bc
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Add stable diffusion weights
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initial commit
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