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J-Douglas/Novelty
Novelty is a image-to-image model from J-Douglas. Use it when you need one image transformed into another. It is set up for diffusers. The card lists the license as mit.
GitHub: https://github.com/timothybrooks/instruct-pix2pix <img src='https://instruct-pix2pix.timothybrooks.com/teaser.jpg'/
Downloads · 30 days
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.bin8.2 GB · 34%
From the Hugging Face model README
GitHub: https://github.com/timothybrooks/instruct-pix2pix <img src='https://instruct-pix2pix.timothybrooks.com/teaser.jpg'/>
To use InstructPix2Pix, install diffusers using main for now. The pipeline will be available in the next release
pip install diffusers accelerate safetensors transformers
import PIL
import requests
import torch
from diffusers import StableDiffusionInstructPix2PixPipeline, EulerAncestralDiscreteScheduler
model_id = "timbrooks/instruct-pix2pix"
pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16, safety_checker=None)
pipe.to("cuda")
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
url = "https://raw.githubusercontent.com/timothybrooks/instruct-pix2pix/main/imgs/example.jpg"
def download_image(url):
image = PIL.Image.open(requests.get(url, stream=True).raw)
image = PIL.ImageOps.exif_transpose(image)
image = image.convert("RGB")
return image
image = download_image(url)
prompt = "turn him into cyborg"
images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=1).images
images[0]