Instructions to use sultan/BioM-ELECTRA-Large-Generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sultan/BioM-ELECTRA-Large-Generator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sultan/BioM-ELECTRA-Large-Generator")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sultan/BioM-ELECTRA-Large-Generator") model = AutoModelForMaskedLM.from_pretrained("sultan/BioM-ELECTRA-Large-Generator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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This model was pre-trained on PubMed Abstracts only with biomedical domain vocabulary for 434K steps with a batch size of 4096 on TPUv3-512 unit.
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```bibtex
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@inproceedings{alrowili-shanker-2021-biom,
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title = "{B}io{M}-Transformers: Building Large Biomedical Language Models with {BERT}, {ALBERT} and {ELECTRA}",
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models.
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This model was pre-trained on PubMed Abstracts only with biomedical domain vocabulary for 434K steps with a batch size of 4096 on TPUv3-512 unit.
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Check our GitHub repo at https://github.com/salrowili/BioM-Transformers for TensorFlow and GluonNLP checkpoints.
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```bibtex
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@inproceedings{alrowili-shanker-2021-biom,
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title = "{B}io{M}-Transformers: Building Large Biomedical Language Models with {BERT}, {ALBERT} and {ELECTRA}",
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