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maitry30/verilang-muril
verilang-muril is a machine learning model from maitry30. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
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.safetensors950 MB · 99%
From the Hugging Face model README
AI-powered fake news detector for WhatsApp forwards in Hindi, Gujarati, Marathi and Telugu using Google's MuRIL model.
WhatsApp misinformation in Indian regional languages is a serious problem affecting millions of people daily. Existing fake news detectors work only for English. VeriLang solves this by detecting misinformation in 4 major Indian languages — Hindi, Gujarati, Marathi and Telugu.
| Feature | Other Projects | VeriLang |
|---|---|---|
| Languages | English only | 4 Indian languages |
| Model | Generic BERT | MuRIL — Indian language specialist |
| Target | General news | WhatsApp forwards specifically |
| Explainability | None | SHAP word importance |
| Deployment | Jupyter only | Live web app |
| Language | Total | Fake | Real |
|---|---|---|---|
| Hindi | 15,051 | 7,599 | 7,452 |
| Gujarati | 14,830 | 6,145 | 8,685 |
| Telugu | 11,424 | 4,795 | 6,629 |
| Marathi | 8,121 | 707 | 7,414 |
| Model | Accuracy |
|---|---|
| Logistic Regression | 99.63% |
| Naive Bayes | 97.77% |
| SVM | 99.84% |
| MuRIL (final) | 99.92% |
| Language | SVM | MuRIL |
|---|---|---|
| Hindi | 99.66% | 99.80% |
| Gujarati | 99.86% | 99.93% |
| Marathi | 99.94% | 100.00% |
| Telugu | 99.96% | 100.00% |
| Model | Train | Test | Gap | Status |
|---|---|---|---|---|
| Logistic Reg | 99.60% | 99.63% | 0.03% | No overfit |
| SVM | 99.99% | 99.84% | 0.15% | No overfit |
| MuRIL | — | 99.92% | — | CV std 0.05% |
| Category | Tools |
|---|---|
| Deep Learning | PyTorch, HuggingFace Transformers |
| Model | google/muril-base-cased |
| ML Baseline | Scikit-learn, TF-IDF |
| Explainability | SHAP |
| Web App | Streamlit |
| Model Hosting | HuggingFace Hub |
| Training | Google Colab T4 GPU |
git clone https://github.com/Maitry09/verilang-misinformation-detector
cd verilang-misinformation-detector
pip install -r requirements.txt
streamlit run app.py
Add .streamlit/secrets.toml:
HF_TOKEN = "your_token_here"
Maitry
MIT License
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