Instructions to use osunlp/BioVocabBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osunlp/BioVocabBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="osunlp/BioVocabBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("osunlp/BioVocabBERT") model = AutoModelForMaskedLM.from_pretrained("osunlp/BioVocabBERT") - Notebooks
- Google Colab
- Kaggle
This biomedical language model uses a specialized biomedical tokenizer which is more closely aligned with human-morphological judgements than previous biomedical tokenizers such as PubMedBERT.
Details about our tokenizer design, pre-training procedure and downstream results can be found in our BioNLP @ ACL 2023 paper