Image-to-Image
Diffusers
image-generation
image-inpainting
reference-based-inpainting
human-product-images
lora
hifi-inpaint
Instructions to use donghao-zhou/HiFi-Inpaint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use donghao-zhou/HiFi-Inpaint 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("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("donghao-zhou/HiFi-Inpaint") 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
- Local Apps Settings
- Draw Things
- Xet hash:
- 1738c76ca66a911b2024ad2ae777e214a463cbad2fe5eae53891b70fc86c079f
- Size of remote file:
- 5.84 kB
- SHA256:
- 68ee6eb667d69b51bb622cde2e9494e7382427ae67492f6a94a080f7e5bbee5b
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