Image Segmentation
Transformers
Safetensors
cond_unet
ultrasound
medical-image-segmentation
attention-unet
custom-pipeline
custom_code
Instructions to use AImageLab-Zip/US_Cond-UNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AImageLab-Zip/US_Cond-UNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="AImageLab-Zip/US_Cond-UNet", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("AImageLab-Zip/US_Cond-UNet", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 72 Bytes
8966f37 | 1 2 3 4 5 6 7 8 9 | transformers>=4.40 torch torchvision safetensors einops ptwt wandb peft |