Research Spotlight
Collection
Research Spotlight is a modular workflow written in Python for converting research publications into an ontology-driven scholarly knowledge graph. • 3 items • Updated
How to use NikosKprl/en_deberta_v3_base_ner_activity with spaCy:
!pip install https://huggingface.co/NikosKprl/en_deberta_v3_base_ner_activity/resolve/main/en_deberta_v3_base_ner_activity-any-py3-none-any.whl
# Using spacy.load().
import spacy
nlp = spacy.load("en_deberta_v3_base_ner_activity")
# Importing as module.
import en_deberta_v3_base_ner_activity
nlp = en_deberta_v3_base_ner_activity.load()A Named Entity Recognition (NER) model specialized in detecting research activities or actions from scholarly publications.
| Feature | Description |
|---|---|
| Name | en_deberta_v3_base_ner_activity |
| Version | 0.1.0 |
| spaCy | >=3.8.7,<3.9.0 |
| Default Pipeline | transformer, ner |
| Components | transformer, ner |
| License | MIT |
| Component | Labels |
|---|---|
ner |
ACTIVITY |
| Type | Score |
|---|---|
ENTS_F |
81.58 |
ENTS_P |
79.23 |
ENTS_R |
84.07 |
Base model
microsoft/deberta-v3-base