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bert-address-en0.1.1
wse-research/bert-address-en0.1.1
bert-address-en0.1.1 is a token classification model from wse-research. Use it when you need labels on individual words, such as names. It is set up for spacy. The card lists the license as mit.
This is a NER-model trained using the spacy library in Python. It recognizes addresses (postal codes, cities, streets and housenumbers) and uses a separate spacy model to find connected entities. It is based on spacy'…
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Updated Apr 24, 2023
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502 MB
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At a glance
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Access
- Public
- Created
- Apr 17, 2023
- Updated
- Apr 24, 2023
- SHA
- 3c027728
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Model card
From the Hugging Face model README
This is a NER-model trained using the spacy library in Python. It recognizes addresses (postal codes, cities, streets and housenumbers) and uses a separate spacy model to find connected entities. It is based on spacy's English transformer pipeline (roberta-base). You can use it as any other spacy model.
This model was created as part of the Qanary-NER-automl-component's multi result branch. To include it in this component, refer to the corresponding Readme chapter. There are images containing this, and other, models already available to download. A list can be found in the final chapter of the Readme.
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Languages
- en
- Created
- Apr 17, 2023
- Updated
- Apr 24, 2023