peluz/lener_br
Updated • 531 • 39
How to use flaviaggp/pt_lg_pipeline with spaCy:
!pip install https://huggingface.co/flaviaggp/pt_lg_pipeline/resolve/main/pt_lg_pipeline-any-py3-none-any.whl
# Using spacy.load().
import spacy
nlp = spacy.load("pt_lg_pipeline")
# Importing as module.
import pt_lg_pipeline
nlp = pt_lg_pipeline.load()Link do trabalho no Kaggle: https://www.kaggle.com/datasets/flaviagg/lenerbr .
Criei um Web App que proporciona a comparação dos modelos sm e lg: https://huggingface.co/spaces/flaviaggp/Streamlit_Lener .
| Feature | Description |
|---|---|
| Name | pt_lg_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.4.4,<3.5.0 |
| 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 |
JURISPRUDENCIA, LEGISLACAO, LOCAL, ORGANIZACAO, PESSOA, TEMPO |
| Type | Score |
|---|---|
ENTS_F |
83.79 |
ENTS_P |
83.98 |
ENTS_R |
83.61 |
TOK2VEC_LOSS |
23620.33 |
NER_LOSS |
127975.46 |