Hugging Face's logo

NikosKprl
/
en_deberta_v3_base_ner_method

Token Classification
spaCy
English
Eval Results (legacy)
Model card Files
xet
 Community
How to use from the
Use from the
spaCy library
!pip install https://huggingface.co/NikosKprl/en_deberta_v3_base_ner_method/resolve/main/en_deberta_v3_base_ner_method-any-py3-none-any.whl

# Using spacy.load().
import spacy
nlp = spacy.load("en_deberta_v3_base_ner_method")

# Importing as module.
import en_deberta_v3_base_ner_method
nlp = en_deberta_v3_base_ner_method.load()

A Named Entity Recognition (NER) model specialized in detecting methods or techniques from scholarly publications.

Feature Description
Name en_deberta_v3_base_ner_method
Version 0.1.0
spaCy >=3.8.7,<3.9.0
Default Pipeline transformer, ner
Components transformer, ner
License MIT

Label Scheme

View label scheme (1 labels for 1 components)
Component Labels
ner METHOD

Accuracy

Type Score
ENTS_F 81.08
ENTS_P 81.40
ENTS_R 80.75
Downloads last month
15
Inference Providers NEW
Token Classification
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for NikosKprl/en_deberta_v3_base_ner_method

Base model

microsoft/deberta-v3-base
Finetuned
(612)
this model

Collection including NikosKprl/en_deberta_v3_base_ner_method

Evaluation results