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 German transformer pipeline (bert-base-german-cased). You can use it as any other spacy-generated transformer 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.
- Downloads last month
- 0
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.