Fix base-encoder link in HF hub
Browse files
README.md
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@@ -34,7 +34,7 @@ widget:
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to invoke Article 155 of the Spanish Constitution over Catalonia after the Catalan
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Parliament declared the independence.
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pipeline_tag: token-classification
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base_model: numind/generic-
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model-index:
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- name: SpanMarker with numind/generic-entity_recognition-v1 on FewNERD
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results:
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@@ -59,13 +59,13 @@ model-index:
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# SpanMarker with numind/generic-entity_recognition-v1 on FewNERD
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This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained on the [FewNERD](https://huggingface.co/datasets/DFKI-SLT/few-nerd) dataset that can be used for Named Entity Recognition. This SpanMarker model uses [numind/generic-
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## Model Details
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### Model Description
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- **Model Type:** SpanMarker
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- **Encoder:** [numind/generic-
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- **Maximum Sequence Length:** 256 tokens
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- **Maximum Entity Length:** 8 words
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- **Training Dataset:** [FewNERD](https://huggingface.co/datasets/DFKI-SLT/few-nerd)
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to invoke Article 155 of the Spanish Constitution over Catalonia after the Catalan
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Parliament declared the independence.
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pipeline_tag: token-classification
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base_model: numind/generic-entity_recognition_NER-v1
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model-index:
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- name: SpanMarker with numind/generic-entity_recognition-v1 on FewNERD
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results:
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# SpanMarker with numind/generic-entity_recognition-v1 on FewNERD
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This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained on the [FewNERD](https://huggingface.co/datasets/DFKI-SLT/few-nerd) dataset that can be used for Named Entity Recognition. This SpanMarker model uses [numind/generic-entity_recognition_NER-v1](https://huggingface.co/numind/generic-entity_recognition_NER-v1) as the underlying encoder.
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## Model Details
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### Model Description
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- **Model Type:** SpanMarker
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- **Encoder:** [numind/generic-entity_recognition_NER-v1](https://huggingface.co/numind/generic-entity_recognition_NER-v1)
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- **Maximum Sequence Length:** 256 tokens
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- **Maximum Entity Length:** 8 words
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- **Training Dataset:** [FewNERD](https://huggingface.co/datasets/DFKI-SLT/few-nerd)
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