Instructions to use microsoft/BiomedVLP-CXR-BERT-specialized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/BiomedVLP-CXR-BERT-specialized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="microsoft/BiomedVLP-CXR-BERT-specialized", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/BiomedVLP-CXR-BERT-specialized", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Ozan Oktay commited on
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Parent(s): d233f2f
use aka.ms link for the repository.
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README.md
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Please refer to the corresponding paper, ["Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing", ECCV'22](https://arxiv.org/abs/2204.09817) for additional details on the model training and evaluation.
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For additional inference pipelines with CXR-BERT, please refer to the [HI-ML-Multimodal GitHub](https://
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Please refer to the corresponding paper, ["Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing", ECCV'22](https://arxiv.org/abs/2204.09817) for additional details on the model training and evaluation.
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For additional inference pipelines with CXR-BERT, please refer to the [HI-ML-Multimodal GitHub](https://aka.ms/biovil-code) repository.
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