README.md

metadata

license: cc-by-sa-4.0
library_name: span-marker
tags:
  - span-marker
  - token-classification
  - ner
  - named-entity-recognition
pipeline_tag: token-classification
widget:
  - text: >-
      Amelia Earthart voló su Lockheed Vega 5B monomotor a través del Océano
      Atlántico hasta París .
    example_title: Spanish
  - text: >-
      Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic
      to Paris .
    example_title: English
  - text: >-
      Amelia Earthart a fait voler son monomoteur Lockheed Vega 5B à travers
      l'ocean Atlantique jusqu'à Paris .
    example_title: French
  - text: >-
      Amelia Earthart flog mit ihrer einmotorigen Lockheed Vega 5B über den
      Atlantik nach Paris .
    example_title: German
  - text: >-
      Амелия Эртхарт перелетела на своем одномоторном самолете Lockheed Vega 5B
      через Атлантический океан в Париж .
    example_title: Russian
  - text: >-
      Amelia Earthart vloog met haar één-motorige Lockheed Vega 5B over de
      Atlantische Oceaan naar Parijs .
    example_title: Dutch
  - text: >-
      Amelia Earthart przeleciała swoim jednosilnikowym samolotem Lockheed Vega
      5B przez Ocean Atlantycki do Paryża .
    example_title: Polish
  - text: >-
      Amelia Earthart flaug eins hreyfils Lockheed Vega 5B yfir Atlantshafið til
      Parísar .
    example_title: Icelandic
  - text: >-
      Η Amelia Earthart πέταξε το μονοκινητήριο Lockheed Vega 5B της πέρα ​​από
      τον Ατλαντικό Ωκεανό στο Παρίσι .
    example_title: Greek
model-index:
  - name: >-
      SpanMarker w. roberta-base on finegrained, supervised FewNERD by Tom
      Aarsen
    results:
      - task:
          type: token-classification
          name: Named Entity Recognition
        dataset:
          type: DFKI-SLT/few-nerd
          name: finegrained, supervised FewNERD
          config: supervised
          split: test
          revision: 2e3e727c63604fbfa2ff4cc5055359c84fe5ef2c
        metrics:
          - type: f1
            value: 0.686
            name: F1
          - type: precision
            value: 0.6847
            name: Precision
          - type: recall
            value: 0.6873
            name: Recall
datasets:
  - DFKI-SLT/few-nerd
language:
  - multilingual
metrics:
  - f1
  - recall
  - precision

SpanMarker for Named Entity Recognition

This is a SpanMarker model that can be used for Named Entity Recognition. In particular, this SpanMarker model uses xlm-roberta-base as the underlying encoder.

Usage

To use this model for inference, first install the span_marker library:

pip install span_marker

You can then run inference with this model like so:

from span_marker import SpanMarkerModel

# Download from the 🤗 Hub
model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-xlm-roberta-base-fewnerd-fine-super")
# Run inference
entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris .")

See the SpanMarker repository for documentation and additional information on this library.