Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use CompVis/stable-diffusion-v1-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CompVis/stable-diffusion-v1-4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") prompt = "A high tech solarpunk utopia in the Amazon rainforest" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`.
#209
by patrickvonplaten - opened
Hey CompVis 👋,
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(CompVis/stable-diffusion-v1-4).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.
patrickvonplaten changed pull request status to merged