SteffRhes/APIS_OEBL__Named_Entity_Recognition
Updated • 12
How to use SteffRhes/de_APIS_OEBL_NER_lg with spaCy:
!pip install https://huggingface.co/SteffRhes/de_APIS_OEBL_NER_lg/resolve/main/de_APIS_OEBL_NER_lg-any-py3-none-any.whl
# Using spacy.load().
import spacy
nlp = spacy.load("de_APIS_OEBL_NER_lg")
# Importing as module.
import de_APIS_OEBL_NER_lg
nlp = de_APIS_OEBL_NER_lg.load()| Feature | Description |
|---|---|
| Name | de_APIS_OEBL_NER_lg |
| Version | 1.0 |
| spaCy | >=3.6.0,<3.7.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 500000 keys, 500000 unique vectors (300 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
| Component | Labels |
|---|---|
ner |
LOC, ORG, PER |
| Type | Score |
|---|---|
ENTS_F |
77.85 |
ENTS_P |
76.71 |
ENTS_R |
79.03 |
TOK2VEC_LOSS |
13266.36 |
NER_LOSS |
378634.81 |
Trained on data originating from the APIS project and the Austrian Biographical Lexicon (ÖBL).
Reproducible training context (model m2): https://github.com/acdh-oeaw/veld_chain_7_train/
Dataset available here: https://huggingface.co/datasets/SteffRhes/APIS_OEBL__Named_Entity_Recognition