Instructions to use lilpotat/sa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lilpotat/sa 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/sa", 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
-
Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`.
Hey lilpotat 👋, Your model repository seems to contain logic to load a feature extractor that is deprecated, which you should notice by seeing the warning: ``` transformers/models/clip/feature_extraction_clip.py:28: FutureWarning: The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please use CLIPImageProcessor instead. warnings.warn( ``` when running `pipe = DiffusionPipeline.from_pretrained(lilpotat/sa)`.This PR makes sure that the warning does not show anymore by replacing `CLIPFeatureExtractor` with `CLIPImageProcessor`. This will certainly not change or break your checkpoint, but onlymake sure that everything is up to date. Best, the 🧨 Diffusers team.b768ed6
-
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. (b6ccf59ad1939c0235551b1fb30bd8f1b4c346cf) Co-authored-by: Patrick von Platen <patrickvonplaten@users.noreply.huggingface.co>c302120
-
Update unet/config.json
d80f987
-
Create README.md
efa4d58 -
pt
108c8bb -
ckpt
e2d1ac8 -
initial commit
34ea03e