Image-to-Image
Diffusers
StableDiffusionImageVariationPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use lambda/sd-image-variations-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lambda/sd-image-variations-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lambda/sd-image-variations-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Commit History
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Add library_name tag, link to paper and project page
Verified signatureThis PR adds the `library_name` and `pipeline_tag` to the metadata. It also adds links to the paper and the project page.5120b3f
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- Update README.md (c4f0213a791520fb3cf50425f54a5e7b00dab316) Co-authored-by: Joshua L Corsen <averad@users.noreply.huggingface.co>42bc0ee
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Merge branch 'main' of https://huggingface.co/lambdalabs/sd-image-variations-diffusers into main
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