Instructions to use darragh/swinunetr-btcv-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use darragh/swinunetr-btcv-tiny with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("darragh/swinunetr-btcv-tiny", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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>>> model = SwinUnetrModelForInference.from_pretrained('darragh/swinunetr-btcv-tiny')
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You can also use `predict.py` to run inference for sample dicom medical images.
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# Limitations and bias
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The training data used for this model is specific to CAT scans from certain health facilities and machines. Data from other facilities may difffer in image distributions, and may require finetuning of the models for best performance.
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>>> model = SwinUnetrModelForInference.from_pretrained('darragh/swinunetr-btcv-tiny')
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```
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# Limitations and bias
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The training data used for this model is specific to CAT scans from certain health facilities and machines. Data from other facilities may difffer in image distributions, and may require finetuning of the models for best performance.
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