Image Segmentation
Transformers
ONNX
English
medical
ultrasound
obstetrics
segmentation
classification
regression
multi-task
intrapartum
labor-monitoring
medsiglip
siglip
clinical-ai
Instructions to use samwell/laborview-medsiglip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use samwell/laborview-medsiglip with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="samwell/laborview-medsiglip")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("samwell/laborview-medsiglip", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c2752dd49e6b235ba16136b7f6e668d615185fc9eacda39841abd7f6810c27f
- Size of remote file:
- 3.53 GB
- SHA256:
- cdca80f231f2cf5dc7ebe5f73830702f4e9bae2cfc44e0ea298b128a78a25003
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