Instructions to use lilpotat/ashleymoore with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lilpotat/ashleymoore with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lilpotat/ashleymoore", 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`. (#3)
- Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (9fee1cfb81317dff746f8832efc5b8cc269be54f)bcba517
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Add `clip_sample=False` to scheduler to make model compatible with DDIM. (#1)
- Add `clip_sample=False` to scheduler to make model compatible with DDIM. (8301875eb205d57d4e983c21e06ec4e0a2e08879) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>dfbe51a
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ashleymoore
0c72035 -
initial commit
76405f5