Instructions to use ckpt/zero123plus-v1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ckpt/zero123plus-v1.1 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("ckpt/zero123plus-v1.1", torch_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
- Xet hash:
- 86cf6cca0bec13949b073bbf4e8b41e4883a8ab1f436d645c37fca7ddfda41d7
- Size of remote file:
- 167 MB
- SHA256:
- 7cfdd672df17db3283633acb3721afc7735927293c2d3bd2bf64939a6dcd950e
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