Post
363
📢 Deligted to share the new version of the bulk-ner which represent a tiny framework that would save you time for deploing NER with any model.
📦: https://pypi.org/project/bulk-ner/0.25.1/
🌟: https://github.com/nicolay-r/bulk-ner
The direct adaptaion of the LM for NER would result in spending signifcant amount of time on formatting your texts according to the NER-model needs.
In particular:
1. Processing CONLL format with B-I-O tags from model outputs
2. Input trimming: long input content might not be completely fitted
The 0.25.1 I made a huge steps forward by providing:
✅ Enhanced integration by providing function for casting extracted enties to your type (see picture below)
✅ Enhanced integration with AREkit pipelines
✅ Simpified API for using (Example using DeepPavlov NER models): https://github.com/nicolay-r/bulk-ner/wiki#api
👏 The code for pipeline deployment is taken from the AREkit project:
https://github.com/nicolay-r/AREkit
📦: https://pypi.org/project/bulk-ner/0.25.1/
🌟: https://github.com/nicolay-r/bulk-ner
The direct adaptaion of the LM for NER would result in spending signifcant amount of time on formatting your texts according to the NER-model needs.
In particular:
1. Processing CONLL format with B-I-O tags from model outputs
2. Input trimming: long input content might not be completely fitted
The 0.25.1 I made a huge steps forward by providing:
✅ Enhanced integration by providing function for casting extracted enties to your type (see picture below)
✅ Enhanced integration with AREkit pipelines
✅ Simpified API for using (Example using DeepPavlov NER models): https://github.com/nicolay-r/bulk-ner/wiki#api
👏 The code for pipeline deployment is taken from the AREkit project:
https://github.com/nicolay-r/AREkit