---
title: Hadith Segmentation
emoji: 💬
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
---

# فاصل الحديث — Hadith Splitter

يقسم نص حديث خام (بدون علامات ترقيم هيكلية) إلى **سند** (سلسلة الرواة) و**متن**
(قول النبي صلى الله عليه وسلم)، ويعرض الحدود بينهما بالألوان على النص الأصلي.

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.