Instructions to use ghoskno/Fake-QRcode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ghoskno/Fake-QRcode 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("ghoskno/Fake-QRcode", 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
Update README.md
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by kharbouch - opened
README.md
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@@ -22,10 +22,10 @@ import numpy as np
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import torch
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import os, sys
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from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, AutoencoderKL,
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from PIL import Image
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controlnet = ControlNetModel.from_pretrained("ghoskno/Fake-Qrcode")
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pipe = StableDiffusionControlNetPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float16
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)
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import torch
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import os, sys
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from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, AutoencoderKL, DDIMScheduler
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from PIL import Image
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controlnet = ControlNetModel.from_pretrained("ghoskno/Fake-Qrcode", torch_dtype=torch.float16)
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pipe = StableDiffusionControlNetPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", controlnet=controlnet, torch_dtype=torch.float16
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)
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