French model for information extraction from Job postings
| Feature |
Description |
| Name |
fr_job_info_extr_fr |
| Version |
0.0.0 |
| spaCy |
>=3.5.1,<3.6.0 |
| Default Pipeline |
tok2vec, ner |
| Components |
tok2vec, ner |
| Vectors |
500000 keys, 500000 unique vectors (300 dimensions) |
| Sources |
n/a |
| License |
n/a |
| Author |
Youssef Chafiqui |
Label Scheme
View label scheme (8 labels for 1 components)
| Component |
Labels |
ner |
CONTRAT, EDUCATION, EXPERIENCE, HARD-SKILL, LANGUE, POSTE, SALAIRE, SOFT-SKILL |
Accuracy
| Type |
Score |
ENTS_F |
96.10 |
ENTS_P |
95.98 |
ENTS_R |
96.22 |
TOK2VEC_LOSS |
219378.28 |
NER_LOSS |
68755.91 |
Usage
Presequities
Install spaCy library
pip install spacy
Download the model
pip install https://huggingface.co/ychafiqui/fr_job_info_extr_fr/resolve/main/fr_job_info_extr_fr-any-py3-none-any.whl
Load the model
import spacy
nlp = spacy.load("fr_job_info_extr_fr")
Inference using the model
doc = nlp('put your job description here')
for ent in doc.ents:
print(ent.text, "-", ent.label_)
