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en_cv_info_extr
ychafiqui/en_cv_info_extr
en_cv_info_extr is a token classification model from ychafiqui. Use it when you need labels on individual words, such as names. It is set up for spacy.
This model is designed for information extraction from resumes/CVs written in English. It employs a transformer-based architecture with spaCy for named entity recognition (NER) tasks. The model aims to parse various s…
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At a glance
- Task
- Token Classification
- Library
- spacy
- Access
- Public
- Created
- Jan 12, 2024
- Updated
- May 30, 2025
- SHA
- d61e91cb
Try a prompt
Model card
From the Hugging Face model README
Information extraction from Resumes/CVs written in English
Model Description
This model is designed for information extraction from resumes/CVs written in English. It employs a transformer-based architecture with spaCy for named entity recognition (NER) tasks. The model aims to parse various sections of resumes, including personal details, education history, professional experience, skills, and certifications, enabling users to extract structured information for further processing or analysis.
Model Details
| Feature | Description |
|---|---|
Language | English |
Task | Named Entity Recognition (NER) |
Objective | Information extraction from resumes/CVs |
Spacy Components | Transformer, Named Entity Recognition (NER) |
Author | Youssef Chafiqui |
NER Entities
The model recognizes various entities corresponding to different sections of a resume. Below are the entities used by the model:
| Label | Description |
|---|---|
| 'FNAME' | First name |
| 'LNAME' | Last name |
| 'ADDRESS' | Address |
| 'CERTIFICATION' | Certification |
| 'EDUCATION' | Education section |
| 'EMAIL' | Email address |
| 'EXPERIENCE' | Experience section |
| 'HOBBY' | Hobby |
| 'HSKILL' | Hard skill |
| 'LANGUAGE' | Language |
| 'PHONE' | Phone number |
| 'PROFILE' | Profile |
| 'PROJECT' | Project section |
| 'SSKILL' | Soft skill |
Evaluation Metrics
| Type | Score |
|---|---|
F1 score | 81.98 |
Precision | 83.33 |
Recall | 80.68 |
Usage
Presequities
Install spaCy library
pip install spacy
Install Transformers library
pip install transformers
Download the model
pip install https://huggingface.co/ychafiqui/en_cv_info_extr/resolve/main/en_cv_info_extr-1.0.0-py3-none-any.whl
Load the model
import spacy
nlp = spacy.load("en_cv_info_extr")
Inference using the model
doc = nlp('put your resume here')
for ent in doc.ents:
print(ent.text, "-", ent.label_)
- Task
- Token Classification
- Library
- spacy
- Languages
- en
- Created
- Jan 12, 2024
- Updated
- May 30, 2025