import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Adapter/t2iadapter", 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]T2I Adapter - SDXL
T2I Adapter is a network providing additional conditioning to stable diffusion. Each t2i checkpoint takes a different type of conditioning as input and is used with a specific base stable diffusion checkpoint.
This checkpoint provides conditioning on sketches for the stable diffusion XL checkpoint.
The Original Recipe Drives SDXL.
| SD-V1.4/1.5 | SD-XL | T2I-Adapter | T2I-Adapter-SDXL | |
|---|---|---|---|---|
| Parameters | 860M | 2.6B | 77 M | 77 M |
Examples and Comparison
Keypoint-guided
Sketch-guided
Canny-guided
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Base model
stabilityai/stable-diffusion-xl-base-1.0