| --- |
| language: |
| - tt |
| license: cc-by-sa-4.0 |
| task_categories: |
| - text-generation |
| - text-classification |
| tags: |
| - instruction-tuning |
| - tatar |
| - grammatical-error-correction |
| - toxicity |
| - emotion |
| - detoxification |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train.parquet |
| - split: test |
| path: data/test.parquet |
| --- |
| |
| # Tatar instructions |
|
|
| A Tatar instruction-tuning dataset in the [InstruCAT](https://huggingface.co/datasets/projecte-aina/InstruCAT) format, |
| with an extra `conversations` column that holds the chat messages as a JSON string. All instructions are in Tatar. |
|
|
| | column | description | |
| |---|---| |
| | `id` | `<source>_<source id>`, e.g. `wikigec_31223` (the index in `wikiedits_tt_gec.parquet`) | |
| | `instruction` | task instruction (Tatar), one of several templates, picked deterministically from the id | |
| | `context` | input text | |
| | `response` | expected answer | |
| | `category` | task category | |
| | `conversations` | JSON string `[{"role": "user", "content": instruction + "\n\n" + context}, {"role": "assistant", "content": response}]` | |
|
|
| | category | train | test | source | |
| |---|---|---|---| |
| | `gec` | 22,541 | 2,506 | [WikiGEC-TT](#) — Tatar Wikipedia edit history 2003–2026, `script=cyrl`, `edit_type=spelling`; split by article (no page in both splits) | |
| | `toxicity_classification` | 4,490 | 500 | [textdetox/multilingual_toxicity_dataset](https://huggingface.co/datasets/textdetox/multilingual_toxicity_dataset) `tt`; stratified 90/10; answers «Әйе»/«Юк» | |
| | `emotion_classification` | 1,193 | 1,000 | [brighter-dataset/BRIGHTER-emotion-categories](https://huggingface.co/datasets/brighter-dataset/BRIGHTER-emotion-categories) `tat`; original splits (train+dev → train, test → test); labels ачу, җирәнү, курку, шатлык, кайгы, гаҗәпләнү / «хис юк» | |
| | `detoxification` | 475 | 120 | [textdetox/multilingual_paradetox_test](https://huggingface.co/datasets/textdetox/multilingual_paradetox_test) `tt`; random 80/20 | |
| | **total** | **28,699** | **4,126** | | |
|
|
| Processing: whitespace normalization, empty rows and rows over 4,000 characters removed, deduplication on |
| `(context, response)`, and a cross-source leakage guard so that no train `context` also occurs in test. |
|
|
| ```python |
| import json |
| from datasets import load_dataset |
| ds = load_dataset("gaydmi/instruct") |
| messages = json.loads(ds["train"][0]["conversations"]) |
| ``` |
|
|
| Notes: |
| * `gec` is silver data mined from human Wikipedia edits. The `spelling` subset is the cleanest part. |
| * The detoxification pairs come from the official TextDetox ParaDetox **test** set. Models trained on its |
| train part should not be evaluated on that benchmark. |
| * Licenses follow the sources: Wikipedia is CC BY-SA 4.0; check the TextDetox and BRIGHTER cards for theirs. |
|
|
