Instructions to use tsantos/PathologyBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tsantos/PathologyBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tsantos/PathologyBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tsantos/PathologyBERT") model = AutoModelForMaskedLM.from_pretrained("tsantos/PathologyBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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## More Information
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Refer to the original paper, [Pre-trained Vs. A New Transformer Language Model for A Specific Domain - Breast Pathology Use-case](https://arxiv.org/) for additional details and masked language performance on Pathology Specimen Reports
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## Hierarchical BERT Classification For Breast Cancer
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## More Information
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Refer to the original paper, [Pre-trained Vs. A New Transformer Language Model for A Specific Domain - Breast Pathology Use-case](https://arxiv.org/abs/2205.06885) for additional details and masked language performance on Pathology Specimen Reports
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## Hierarchical BERT Classification For Breast Cancer
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