Text Classification
Joblib
sentence-transformers
scikit-learn
embeddings
job-scam-detection
internship
Instructions to use agnialf/Internships-entrylevel-job-scam-svm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use agnialf/Internships-entrylevel-job-scam-svm with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("agnialf/Internships-entrylevel-job-scam-svm") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Internship and Entry-Level Job Scam Classifier
This model classifies internship and entry-level job postings into three scam-risk categories:
legitimatesuspiciousfraudulent
It was trained for an embeddings-based text classification project. The model uses sentence embeddings from sentence-transformers/all-MiniLM-L6-v2 and a Linear SVM classifier.
Model Details
The final classifier is:
sentence-transformers/all-MiniLM-L6-v2 embeddings + Linear SVM classifier