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Update app.py
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app.py
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@@ -122,10 +122,12 @@ def ner(
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with gr.Blocks(title="GLiNER-M-v2.1") as demo:
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gr.Markdown(
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"""
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# GLiNER-
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GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios.
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## Links
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* Model: https://huggingface.co/urchade/gliner_multi-v2.1
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with gr.Blocks(title="GLiNER-M-v2.1") as demo:
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gr.Markdown(
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"""
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# GLiNER-PII (Personnally Identifiable Information extraction)
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GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios.
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The model has been trained by fine-tuning urchade/gliner_multi-v2.1 on the urchade/synthetic-pii-ner-mistral-v1 dataset.
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## Links
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* Model: https://huggingface.co/urchade/gliner_multi-v2.1
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