Fill-Mask
Transformers
PyTorch
Safetensors
English
modernbert
masked-lm
long-context
BioClinical-ModernBERT
clinical
biomedical
clinical encoder
clinical modern bert
Instructions to use thomas-sounack/BioClinical-ModernBERT-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thomas-sounack/BioClinical-ModernBERT-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="thomas-sounack/BioClinical-ModernBERT-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("thomas-sounack/BioClinical-ModernBERT-large") model = AutoModelForMaskedLM.from_pretrained("thomas-sounack/BioClinical-ModernBERT-large", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ffa9fbd0ed3a91d00583c966ef3bbabe434a645756b91b3c2120b44ec80c4761
- Size of remote file:
- 1.58 GB
- SHA256:
- 620d0bc102287e8942e143f46db29a63e9a2306d75acceea0d4bc72857c0a0b7
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