Token Classification
SpanMarker
PyTorch
TensorBoard
English
ner
named-entity-recognition
generated_from_span_marker_trainer
Eval Results (legacy)
Instructions to use tomaarsen/span-marker-bert-base-uncased-keyphrase-inspec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use tomaarsen/span-marker-bert-base-uncased-keyphrase-inspec with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-bert-base-uncased-keyphrase-inspec") - Notebooks
- Google Colab
- Kaggle
Add training script link
Browse files
README.md
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# SpanMarker with bert-base-uncased on Inspec
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This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained on the [Inspec](https://huggingface.co/datasets/midas/inspec) dataset that can be used for Named Entity Recognition. This SpanMarker model uses [bert-base-uncased](https://huggingface.co/models/bert-base-uncased) as the underlying encoder.
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## Model Details
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# SpanMarker with bert-base-uncased on Inspec
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This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained on the [Inspec](https://huggingface.co/datasets/midas/inspec) dataset that can be used for Named Entity Recognition. This SpanMarker model uses [bert-base-uncased](https://huggingface.co/models/bert-base-uncased) as the underlying encoder. See [train.py](train.py) for the training script.
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## Model Details
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