Instructions to use ericntay/stbl_clinical_bert_ft_rs2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ericntay/stbl_clinical_bert_ft_rs2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ericntay/stbl_clinical_bert_ft_rs2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ericntay/stbl_clinical_bert_ft_rs2") model = AutoModelForTokenClassification.from_pretrained("ericntay/stbl_clinical_bert_ft_rs2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ericntay/stbl_clinical_bert_ft_rs2: direct link, hf CLI and curl.
- Browser
- Download file 669 kB
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https://huggingface.co/ericntay/stbl_clinical_bert_ft_rs2/resolve/main/tokenizer.json
- Command line
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hf download hf://ericntay/stbl_clinical_bert_ft_rs2/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/ericntay/stbl_clinical_bert_ft_rs2/resolve/main/tokenizer.json
669 kB
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