Instructions to use ModelsLab/zero123plus-v1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ModelsLab/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("ModelsLab/zero123plus-v1.1", 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:
- 1304b1f372f6b7799b0651cb76d8ad47de8c523cb9ab33314945149fbacdb697
- Size of remote file:
- 1.26 GB
- SHA256:
- 0c626d61a7660d2f86a1f0b5f74f513f93789a99469f1af641cc1f77810427f7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.