Instructions to use trangannh/job-recommendation-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use trangannh/job-recommendation-model with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("trangannh/job-recommendation-model", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Job Recommendation Model
This repository contains a job recommendation model based on skills and majors.
Run model
Change csv file path and run "RECOMMENDATION MODEL" part in Job_Recommendation_System.ipynb notebook
Test recommeded system
In TEST RECOMMENDED SYSTEM part of Job_Recommendation_System.ipynb notebook, change input_hard_skills, input_soft_skills, input_major and run code to receive result
import pickle
import pandas as pd
# Load the model
with open('recommendation_pipeline.pkl', 'rb') as file:
recommendation_pipeline = pickle.load(file)
# Example input
input_data = pd.DataFrame({
'final_hard_skill': ["Python, Java, Finance, Excel"],
'final_soft_skill': ["Communication, Teamwork"],
'candidate_field': [""]
})
# Make recommendations
recommended_jobs = recommendation_pipeline.transform(input_data)
print("Recommended Jobs based on input skills and major:")
print(recommended_jobs)
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