Instructions to use millionlive765/ntest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use millionlive765/ntest with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("millionlive765/ntest", 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 `scale_factor` to vae config. (#3)
- Add `scale_factor` to vae config. (d7a9c77fe18db0a8e47d651a960199043eb6cacc) Co-authored-by: Suraj Patil <valhalla@users.noreply.huggingface.co>7be1972
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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. (fe565a94671479f4cf03640d41b4d1022df08ea0) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>f1a9b3e
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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 (b169ea6de4e2a5d5bd22a672366da2aa4ace0fc6) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>d177fa1
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initial commit
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