Instructions to use Jaeyong21/diffusion_fingervein with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jaeyong21/diffusion_fingervein with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Jaeyong21/diffusion_fingervein", 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:
- 185d705219109c489f07f4964e21e57d5edc20582a4a55b7d7f78dd34e43f6c3
- Size of remote file:
- 1.36 GB
- SHA256:
- e978c401b400c085c2c3054ff4255cffa8d6a31e655afe40487f7e1cf5d9e1dd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.