README.md

---
license: cc-by-nc-sa-4.0
pretty_name: "islamlab — Islamic Sciences Training Sets"
language:
  - ar
task_categories:
  - text-generation
  - text-retrieval
  - question-answering
size_categories:
  - 1M<n<10M
tags:
  - islam
  - arabic
  - classical-arabic
  - continued-pretraining
  - retrieval
  - citation
  - rag
configs:
  - config_name: cpt
    default: true
    data_files:
    - split: train
      path: cpt/train-*.parquet
  - config_name: retrieval
    data_files:
    - split: train
      path: retrieval/train-*.parquet
  - config_name: attribution
    data_files:
    - split: train
      path: attribution/train-*.parquet
  - config_name: eval_retrieval
    data_files:
    - split: test
      path: eval_retrieval/test-*.parquet
  - config_name: eval_attribution
    data_files:
    - split: test
      path: eval_attribution/test-*.parquet
---

# islamlab — Islamic Sciences Training Sets

Training data derived from
[`islamlab/islamic-sciences`](https://huggingface.co/datasets/islamlab/islamic-sciences):
text for domain adaptation, retrieval pairs with hard negatives, and citation
questions whose answers are read out of the corpus rather than written by a
model.

> **Nothing here is generated.** Questions come from a fixed set of templates
> and every answer is a field already present in the corpus. That buys a
> narrow dataset in exchange for one that cannot teach a model a fact the
> sources do not contain.

## Subsets

| config | split | rows | what it is |
|---|---|---:|---|
| `cpt` | train | 780,149 | Apparatus-free, deduplicated text with a provenance header — 3.21B characters |
| `retrieval` | train | 906,691 | A section heading as the query, a passage from that section as the positive, and hard negatives drawn from elsewhere in the same book |
| `attribution` | train | 130,825 | Citation questions with exact answers |
| `eval_retrieval` | test | 26,933 | Same shape, held-out works only |
| `eval_attribution` | test | 32,895 | Same shape, held-out works only |

## The held-out split

The holdout is at the level of the **work**, not the row: 118 of the
4,022 works are assigned to evaluation by a hash of their identifier,
and no line of their text appears in `cpt`, `retrieval` or `attribution`. A
model trained on the train configs has therefore never read the books it is
evaluated on. The assignment is deterministic, so it is the same for everyone.

## The tasks in `attribution`

| task | question | rows (train) |
|---|---|---:|
| `author` | من مؤلف هذا النص؟ | 26,165 |
| `title` | من أي كتاب أُخذ هذا النص؟ | 26,165 |
| `science` | في أي علم يُصنَّف هذا الكتاب؟ | 26,165 |
| `century` | في أي قرن هجري توفي المؤلف؟ | 26,165 |
| `locus` | في أي جزء وصفحة يقع هذا النص؟ | 26,165 |

`messages` is a JSON-encoded chat turn — parse it with `json.loads`. `answer`
holds the exact expected string. The `locus` task deliberately includes the
honest negative: where the source records no pagination, the answer is
*لم تُثبَت الصفحة في هذه النسخة* rather than an invented page.

## Retrieval negatives

Negatives come from **the same book** as the positive, which is what makes
them hard: a chapter of al-Ḥāwī al-Kabīr is separated from another chapter of
al-Ḥāwī al-Kabīr by subject alone, not by vocabulary, register or period.
`negatives` is a JSON-encoded list of strings.

```python
import json
from datasets import load_dataset

d = load_dataset("islamlab/islamic-sciences-training", "retrieval", split="train")
row = d[0]
negatives = json.loads(row["negatives"])
```

## Where this sits

| Dataset | What it holds |
|---|---|
| [`islamlab/islamic-sciences`](https://huggingface.co/datasets/islamlab/islamic-sciences) | The corpus itself — eight sciences, 4,022 works |
| **`islamlab/islamic-sciences-training`** | The training products above |
| [`quranlab/*`](https://huggingface.co/quranlab) · [`risaleinur/*`](https://huggingface.co/risaleinur) | Qur'an and hadith; the Risale-i Nur corpus |

## License

Derived from a corpus licensed **CC BY-NC-SA 4.0**, and carries the same
terms. Credits are in
[`SOURCES.md`](https://huggingface.co/datasets/islamlab/islamic-sciences/blob/main/SOURCES.md)
on the corpus, which is where the works themselves are acknowledged.

## Citation

```bibtex
@misc{islamlab_islamic_sciences_training,
  title  = {islamlab — Islamic Sciences Training Sets},
  author = {islamlab contributors},
  year   = {2026},
  howpublished = {Hugging Face Datasets}
}
```