Token Classification
Transformers
PyTorch
English
bert
sequence-tagger-model
pubmedbert
uncased
radiology
biomedical
bdf-toolbox
Instructions to use StanfordAIMI/stanford-deidentifier-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StanfordAIMI/stanford-deidentifier-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="StanfordAIMI/stanford-deidentifier-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("StanfordAIMI/stanford-deidentifier-base") model = AutoModel.from_pretrained("StanfordAIMI/stanford-deidentifier-base") - Inference
- Notebooks
- Google Colab
- Kaggle
Add TF weights
#1
by Rocketknight1 HF Staff - opened
- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:e6e2a9f005dd3fd100abae86122564b8d26588529e5335b6fa37c4ed904f7c43
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size 435864552
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