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| title: Hadith Segmentation | |
| emoji: ๐ฌ | |
| colorFrom: yellow | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 6.31.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| short_description: Split a raw hadith into sanad and matn | |
| models: | |
| - SHK4K/hadith-segmentation-bert | |
| language: | |
| - ar | |
| tags: | |
| - hadith | |
| - sanad | |
| - matn | |
| - arabic | |
| - token-classification | |
| - digital-humanities | |
| # ูุงุตู ุงูุญุฏูุซ โ Hadith Splitter | |
| ููุณู ูุต ุญุฏูุซ ุฎุงู (ุจุฏูู ุนูุงู ุงุช ุชุฑููู ูููููุฉ) ุฅูู **ุณูุฏ** (ุณูุณูุฉ ุงูุฑูุงุฉ) ู**ู ุชู** | |
| (ููู ุงููุจู ุตูู ุงููู ุนููู ูุณูู )ุ ููุนุฑุถ ุงูุญุฏูุฏ ุจูููู ุง ุจุงูุฃููุงู ุนูู ุงููุต ุงูุฃุตูู. | |
| Splits a raw hadith string into its **sanad** (chain of narrators) and **matn** | |
| (the saying itself), and highlights the boundary on the original text. | |
| - Model: [SHK4K/hadith-segmentation-bert](https://huggingface.co/SHK4K/hadith-segmentation-bert) | |
| (AraBERT v02 fine-tuned for token classification) | |
| - Labels: `B-SANAD`, `I-SANAD`, `B-MATN`, `I-MATN`, reduced to a single cut | |
| - Diacritics are stripped for inference (the model was trained undiacritized) | |
| and mapped back, so the output keeps your original vocalized text | |
| - Long hadiths: processed in overlapping 512-token windows (stride 128) with | |
| per-word majority voting, so nothing is truncated | |
| - Output strings are sliced from your original text, so punctuation and spacing | |
| are preserved | |
| ## Limits | |
| - Accuracy is limited on unusual orthography; the model was trained on | |
| normalized Arabic, and the app normalizes before inference. | |
| - Pastes longer than ~25k subword tokens are processed only up to that point. | |
| - The model is small (0.1B); treat the boundary as a suggestion on | |
| low-resource texts, not ground truth. | |