Instructions to use MLforHealthcare/sam2rad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MLforHealthcare/sam2rad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="MLforHealthcare/sam2rad")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MLforHealthcare/sam2rad", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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- facebook/sam2-hiera-tiny
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pipeline_tag: image-segmentation
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---
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library_name: transformers
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tags:
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base_model:
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- facebook/sam2-hiera-tiny
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pipeline_tag: image-segmentation
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datasets:
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- MLforHealthcare/ACDCPreprocessed
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library_name: transformers
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tags:
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