
# 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 [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) as the underlying encoder. 

## Note
This model is primarily used for efficient tests on the [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) GitHub repository.

## 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-bert-tiny-fewnerd-coarse-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.
{"language": ["en"], "license": "apache-2.0", "library_name": "span-marker", "tags": ["span-marker", "token-classification", "ner", "named-entity-recognition"], "datasets": ["DFKI-SLT/few-nerd"], "metrics": ["f1", "recall", "precision"], "pipeline_tag": "token-classification", "widget": [{"text": "Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.", "example_title": "Amelia Earhart"}, {"text": "Leonardo di ser Piero da Vinci painted the Mona Lisa based on Italian noblewoman Lisa del Giocondo.", "example_title": "Leonardo da Vinci"}], "base_model": "prajjwal1/bert-tiny", "model-index": [{"name": "SpanMarker w. bert-base-cased on coarsegrained, supervised FewNERD by Tom Aarsen", "results": [{"task": {"type": "token-classification", "name": "Named Entity Recognition"}, "dataset": {"name": "coarsegrained, supervised FewNERD", "type": "DFKI-SLT/few-nerd", "config": "supervised", "split": "test", "revision": "2e3e727c63604fbfa2ff4cc5055359c84fe5ef2c"}, "metrics": [{"type": "f1", "value": 0.7081, "name": "F1"}, {"type": "precision", "value": 0.7378, "name": "Precision"}, {"type": "recall", "value": 0.6808, "name": "Recall"}]}]}]}
span-marker pytorch safetensors token-classification ner named-entity-recognition en dataset:DFKI-SLT/few-nerd base_model:prajjwal1/bert-tiny license:apache-2.0 model-index region:us
TAGS
#span-marker #pytorch #safetensors #token-classification #ner #named-entity-recognition #en #dataset-DFKI-SLT/few-nerd #base_model-prajjwal1/bert-tiny #license-apache-2.0 #model-index #region-us 


# SpanMarker for Named Entity Recognition

This is a SpanMarker model that can be used for Named Entity Recognition. In particular, this SpanMarker model uses prajjwal1/bert-tiny as the underlying encoder. 

## Note
This model is primarily used for efficient tests on the SpanMarker GitHub repository.

## Usage

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



You can then run inference with this model like so:



See the SpanMarker repository for documentation and additional information on this library.
# SpanMarker for Named Entity Recognition

This is a SpanMarker model that can be used for Named Entity Recognition. In particular, this SpanMarker model uses prajjwal1/bert-tiny as the underlying encoder. ## Note
This model is primarily used for efficient tests on the SpanMarker GitHub repository. ## Usage

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



You can then run inference with this model like so:



See the SpanMarker repository for documentation and additional information on this library.
TAGS
#span-marker #pytorch #safetensors #token-classification #ner #named-entity-recognition #en #dataset-DFKI-SLT/few-nerd #base_model-prajjwal1/bert-tiny #license-apache-2.0 #model-index #region-us 
 # SpanMarker for Named Entity Recognition

This is a SpanMarker model that can be used for Named Entity Recognition. In particular, this SpanMarker model uses prajjwal1/bert-tiny as the underlying encoder. ## Note
This model is primarily used for efficient tests on the SpanMarker GitHub repository. ## Usage

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



You can then run inference with this model like so:



See the SpanMarker repository for documentation and additional information on this library.
TAGS
#span-marker #pytorch #safetensors #token-classification #ner #named-entity-recognition #en #dataset-DFKI-SLT/few-nerd #base_model-prajjwal1/bert-tiny #license-apache-2.0 #model-index #region-us 
# SpanMarker for Named Entity Recognition

This is a SpanMarker model that can be used for Named Entity Recognition. In particular, this SpanMarker model uses prajjwal1/bert-tiny as the underlying encoder.## Note
This model is primarily used for efficient tests on the SpanMarker GitHub repository.## Usage

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



You can then run inference with this model like so:



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