tomaarsen HF staff commited on
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Upload model

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README.md ADDED
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+
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+ ---
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+ license: apache-2.0
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+ library_name: span-marker
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+ tags:
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+ - span-marker
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+ - token-classification
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+ - ner
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+ - named-entity-recognition
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+ pipeline_tag: token-classification
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+ ---
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+
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+ # SpanMarker for Named Entity Recognition
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+
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+ This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model that can be used for Named Entity Recognition. In particular, this SpanMarker model uses [roberta-large](https://huggingface.co/roberta-large) as the underlying encoder.
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+
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+ ## Usage
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+
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+ To use this model for inference, first install the `span_marker` library:
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+
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+ ```bash
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+ pip install span_marker
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+ ```
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+
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+ You can then run inference with this model like so:
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+
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+ ```python
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+ from span_marker import SpanMarkerModel
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+
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+ # Download from the 🤗 Hub
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+ model = SpanMarkerModel.from_pretrained("span_marker_model_name")
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+ # Run inference
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+ entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.")
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+ ```
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+
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+ See the [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) repository for documentation and additional information on this library.
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config.json ADDED
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+ {
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+ "_name_or_path": "models\\rl-ontonotes-256-128-10-no-context-0\\checkpoint-final",
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+ "architectures": [
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+ "SpanMarkerModel"
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+ ],
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+ "encoder": {
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+ "_name_or_path": "roberta-large",
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+ "add_cross_attention": false,
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+ "architectures": [
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+ "RobertaForMaskedLM"
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+ ],
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+ "1": "B-CARDINAL",
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+ "2": "B-DATE",
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+ "3": "I-DATE",
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+ "4": "B-PERSON",
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+ "7": "B-GPE",
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+ "9": "B-LAW",
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+ "10": "I-LAW",
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+ "11": "B-ORG",
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+ "12": "I-ORG",
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+ "13": "B-PERCENT",
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+ "14": "I-PERCENT",
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+ "15": "B-ORDINAL",
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+ "16": "B-MONEY",
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