Feature Extraction
Transformers
Safetensors
English
bert
fill-mask
biomedical-text
nlp
biomedical-nlp
discharge-notes
healthcare
pubmed
text-embeddings-inference
Instructions to use Simonlee711/Clinical_ModernBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Simonlee711/Clinical_ModernBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Simonlee711/Clinical_ModernBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Simonlee711/Clinical_ModernBERT") model = AutoModelForMaskedLM.from_pretrained("Simonlee711/Clinical_ModernBERT") - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -83,7 +83,7 @@ The source code can be found here: [Clinical ModernBERT Github](https://github.c
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Citing Model
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```
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@misc{simon_lee_2025,
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author = { Simon Lee },
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title = { Clinical_ModernBERT (Revision 24e72d6) },
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year = 2025,
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url = { https://huggingface.co/Simonlee711/Clinical_ModernBERT },
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Citing Model
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```
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@misc{simon_lee_2025,
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author = { Simon A. Lee },
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title = { Clinical_ModernBERT (Revision 24e72d6) },
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year = 2025,
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url = { https://huggingface.co/Simonlee711/Clinical_ModernBERT },
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