
This is a Polish NER system trained using a Frustratingly Easy Domain Adaptation architecture. It is based on Polish BERT and supports different tagsets all using IOBES formats:
1. Wikiann (LOC, PER, ORG)
2. SlavNER 19/21 (EVT, LOC, ORG, PER, PRO)
5. KPWr (EVT, LOC, ORG, PER, PRO)
6. NKJP (DATE, GEOPOLIT, LOC, ORG, PER, TIME)

PER: person, LOC: location, ORG: organization, EVT: event, PRO: product, MISC: Miscellaneous, MEDIA: media, ART: Artifact, TIME: time, DATE: date, GEOPOLIT: Geopolitical

You can select the tagset to use in the output by configuring the model. This model manages differently uppercase words.

More information about the model can be found in the paper (https://aclanthology.org/2021.bsnlp-1.12.pdf) and GitHub repository (https://github.com/EMBEDDIA/NER_FEDA).
{"language": ["pl"], "license": "mit", "tags": ["polish_bert", "ner"]}
transformers pytorch bert polish_bert ner pl license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #polish_bert #ner #pl #license-mit #endpoints_compatible #region-us 


This is a Polish NER system trained using a Frustratingly Easy Domain Adaptation architecture. It is based on Polish BERT and supports different tagsets all using IOBES formats:
1. Wikiann (LOC, PER, ORG)
2. SlavNER 19/21 (EVT, LOC, ORG, PER, PRO)
5. KPWr (EVT, LOC, ORG, PER, PRO)
6. NKJP (DATE, GEOPOLIT, LOC, ORG, PER, TIME)

PER: person, LOC: location, ORG: organization, EVT: event, PRO: product, MISC: Miscellaneous, MEDIA: media, ART: Artifact, TIME: time, DATE: date, GEOPOLIT: Geopolitical

You can select the tagset to use in the output by configuring the model. This model manages differently uppercase words.

More information about the model can be found in the paper (URL and GitHub repository (URL
TAGS
#transformers #pytorch #bert #polish_bert #ner #pl #license-mit #endpoints_compatible #region-us 

TAGS
#transformers #pytorch #bert #polish_bert #ner #pl #license-mit #endpoints_compatible #region-us 
