Token Classification
Transformers
PyTorch
TensorBoard
electra
Generated from Trainer
Eval Results (legacy)
Instructions to use chintagunta85/electramed-small-deid2014-ner-v5-classweights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chintagunta85/electramed-small-deid2014-ner-v5-classweights with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="chintagunta85/electramed-small-deid2014-ner-v5-classweights")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("chintagunta85/electramed-small-deid2014-ner-v5-classweights") model = AutoModelForTokenClassification.from_pretrained("chintagunta85/electramed-small-deid2014-ner-v5-classweights", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4080385727998e42dff63bb3d9db39aa528fbd7e803649e4ea170432ae2ebe3
- Size of remote file:
- 54 MB
- SHA256:
- b3fc7511b8824044ea0c60d69409f370af8bb5896d9f17b15d28de6ff98955b4
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