Instructions to use vdo/hallo2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vdo/hallo2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vdo/hallo2", 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
- Xet hash:
- ce8f8a39a5f0f9522c7a84aacf9a368fc988fdefac16b95536593415f92f64c1
- Size of remote file:
- 255 MB
- SHA256:
- 4d1c6741b3cffcbdc2cd1a12b2c3c2442282e042d5de66909cb643d4fa31b20f
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