--- 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: 0.6860 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](https://github.com/tomaarsen/SpanMarkerNER) model that can be used for Named Entity Recognition. In particular, this SpanMarker model uses [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) as the underlying encoder. ## Usage To use this model for inference, first install the `span_marker` library: ```bash pip install span_marker ``` You can then run inference with this model like so: ```python 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](https://github.com/tomaarsen/SpanMarkerNER) repository for documentation and additional information on this library.