Instructions to use GD-ML/Omni-Effects with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GD-ML/Omni-Effects with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("GD-ML/Omni-Effects", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Add pipeline tag, library name, and link to code
#1
by nielsr HF Staff - opened
This PR improves the model card by:
- Adding the
pipeline_tag: image-to-video, which helps users discover the model via the Hub's pipeline filters (https://huggingface.co/models?pipeline_tag=image-to-video). - Adding the
library_name: diffusers, enabling the "how to use" widget on the model page. - Adding an explicit link to the GitHub code repository.