Instructions to use GaggiX/testWd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GaggiX/testWd with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("GaggiX/testWd", 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
- Draw Things
- DiffusionBee
Correct `sample_size` of Stable Diffusion 1's unet to have correct width and height default
#1
by patrickvonplaten - opened
Since diffusers==0.9.0 the width and height is automatically inferred from the sample_size attribute of your unet's config. It seems like your diffusion model has the same architecture as Stable Diffusion 1 which means that when using this model, by default an image size of 512x512 should be generated. This in turn means the unet's sample size should be 64.
In order to suppress to update your configuration on the fly and to suppress the deprecation warning added in this PR: https://github.com/huggingface/diffusers/pull/1406/files#r1035703505 it is strongly recommended to merge this PR.
GaggiX changed pull request status to merged