Instructions to use MochunniaN1/One-to-All-1.3b_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MochunniaN1/One-to-All-1.3b_2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MochunniaN1/One-to-All-1.3b_2", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
create a space?
#2
by gueriliartener - opened
Hi is it possible to create a space using this or an other of the 3 models?
Sorry, no plans to create a Space for this at the moment.
If you don't have a GPU available, you can still try it free on Kaggle using their 16 GB T4 GPU.
A step-by-step guide here:
https://ncn0ojsozocg.feishu.cn/wiki/J9Ohwmtudin0vtkuyPccIZkhnZz