RockENZO/NLP-Cyber-Harm-Detection
Developed transformer-based fraud detection using BERT, DistilBERT, FLAN‑T5, and BART to classify multiple scam types with explainable outputs. Optimized models for fast, resource‑efficient inference and built production‑ready pipelines with integrated reasoning and scalable deployment. Sources
Stars
2
Forks
—
Language
Jupyter Notebook
License
—
Category
Last pushed
Nov 18, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/RockENZO/NLP-Cyber-Harm-Detection"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
jklu-jaipur/Political-Biasness-Detection
Our ML model calculates the biasness of a political article based on linguistic features and...
yamanalab/why-darkpattern
[Proc of IEEE BigData 2023] Why is the User Interface a Dark Pattern? : Explainable...
davidsvy/Neural-Scam-Artist
Web Scraping, Document Deduplication & GPT-2 Fine-tuning with a newly created scam dataset.
sdarjunwadkar/Political-Idealogies-Prediction-in-News-Articles
Media diversity shapes perspectives, yet biased news distorts reality, fostering misinformation....
nerdimite/bert-web-app
Code for the FullStack AI Live Coding Series- Part 2 (CellStrat AI Lab)