guishe commited on
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e069e5c
1 Parent(s): 0444e15

Fix base-encoder link in HF hub

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  1. README.md +3 -3
README.md CHANGED
@@ -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-entity_recognition-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:
@@ -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-entity_recognition-v1](https://huggingface.co/numind/generic-entity_recognition-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-v1](https://huggingface.co/numind/generic-entity_recognition-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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  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)