Fill-Mask
Transformers
Safetensors
English
modernbert
biomedical
clinical
encoder
Eval Results (legacy)
Instructions to use almanach/ModernBERT-bio-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use almanach/ModernBERT-bio-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="almanach/ModernBERT-bio-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("almanach/ModernBERT-bio-base") model = AutoModelForMaskedLM.from_pretrained("almanach/ModernBERT-bio-base") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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# cpt-en-base
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*cpt-en-base is available in two sizes: [base](https://huggingface.co/rntc/cpt-en-base) (149M parameters) and [large](https://huggingface.co/almanach/cpt-en-large) (396M parameters). Our code is available in our [GitHub repository](https://github.com/Rian-T/colm2026-clm-detour).*
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## Table of Contents
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## Citation
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```bibtex
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@inproceedings{
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title={
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author={
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booktitle={
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year={2026}
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}
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```
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## Acknowledgments
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# cpt-en-base
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## Table of Contents
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## Citation
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```bibtex
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@inproceedings{anonymous2026clm,
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title={Under review},
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author={Anonymous},
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booktitle={Under review},
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year={2026}
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}
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```
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## Acknowledgments
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