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
Epoch 2
Browse files- .gitattributes +1 -0
- finger_vein/0002.png +3 -0
- logs/train_example/events.out.tfevents.1696399789.ubuntu.1247.0 +2 -2
- logs/train_example/events.out.tfevents.1696400308.ubuntu.1576.0 +3 -0
- logs/train_example/events.out.tfevents.1696400382.ubuntu.1756.0 +3 -0
- logs/train_example/events.out.tfevents.1696400980.ubuntu.2117.0 +3 -0
- logs/train_example/events.out.tfevents.1696401045.ubuntu.2297.0 +3 -0
- logs/train_example/events.out.tfevents.1696401144.ubuntu.2477.0 +3 -0
- logs/train_example/events.out.tfevents.1696401216.ubuntu.2657.0 +3 -0
- model_weights_epoch_2.pt +3 -0
- unet/diffusion_pytorch_model.safetensors +1 -1
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