Instructions to use lowem1/cms-ext-Bio_ClinicalBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lowem1/cms-ext-Bio_ClinicalBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lowem1/cms-ext-Bio_ClinicalBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lowem1/cms-ext-Bio_ClinicalBERT") model = AutoModelForMaskedLM.from_pretrained("lowem1/cms-ext-Bio_ClinicalBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from lowem1/cms-ext-Bio_ClinicalBERT: direct link, hf CLI and curl.
- Browser
- Download file 15.9 MB
-
https://huggingface.co/lowem1/cms-ext-Bio_ClinicalBERT/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://lowem1/cms-ext-Bio_ClinicalBERT@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/lowem1/cms-ext-Bio_ClinicalBERT/resolve/refs%2Fpr%2F1/tokenizer.json
15.9 MB
- Xet hash:
- 9c211a2f68746d34563ca3958dd6763fda9a24faab0fb90c774c3807d0d8ace9
- Size of remote file:
- 15.9 MB
- SHA256:
- c60a36279696cba8f5bdcc1b4a016130278b5139b1f74e7c8d0479a6da9e2f7e
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