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This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained on the [Acronym Identification](https://huggingface.co/datasets/acronym_identification) dataset that can be used for Named Entity Recognition. This SpanMarker model uses [bert-base-uncased](https://huggingface.co/bert-base-uncased) as the underlying encoder. See [train.py](train.py) for the training script.
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Is your data always capitalized correctly? Then consider using the cased variant of this model instead for better performance: tomaarsen/span-marker-bert-base-acronyms.
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## Model Details
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This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained on the [Acronym Identification](https://huggingface.co/datasets/acronym_identification) dataset that can be used for Named Entity Recognition. This SpanMarker model uses [bert-base-uncased](https://huggingface.co/bert-base-uncased) as the underlying encoder. See [train.py](train.py) for the training script.
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Is your data always capitalized correctly? Then consider using the cased variant of this model instead for better performance: [tomaarsen/span-marker-bert-base-acronyms](https://huggingface.co/tomaarsen/span-marker-bert-base-acronyms).
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## Model Details
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