Datasets:
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: ValueError
Message: Bad split: pashto_train_instruction. Available splits: ['train', 'validation']
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 61, in get_rows
ds = load_dataset(
^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1705, in load_dataset
return builder_instance.as_streaming_dataset(split=split)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1117, in as_streaming_dataset
raise ValueError(f"Bad split: {split}. Available splits: {list(splits_generators)}")
ValueError: Bad split: pashto_train_instruction. Available splits: ['train', 'validation']Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
ZamAI Pashto Dataset (Cleaned)
Dataset Summary
This repository hosts a cleaned and QC'ed slice of the ZamAI Pashto corpus. The release contains 28,650 Pashto-language articles and prompts that have been deduplicated, normalised, and aligned for instruction-style training as well as prompt/completion workflows.
Dataset Details
- Curated by: ZamAI Team
- Language(s): Pashto (ps)
- License: Apache-2.0
- Version: v1.0 (2025-06-23)
- Sources: BBC Pashto, Radio Azadi, community-contributed Pashto corpora
- Processing Pipeline: ZamAI Pashto Data Processing Pipeline
Dataset Structure
- CSV splits:
pashto_cleaned_train.csv,pashto_cleaned_val.csv,pashto_cleaned_full_dataset.csv - Instruction JSONL:
pashto_train_instruction.jsonl,pashto_val_instruction.jsonl - Prompt/Completion JSONL:
pashto_train_prompt_completion.jsonl,pashto_val_prompt_completion.jsonl
Fields
| Field | Description |
|---|---|
title |
Source headline or generated title |
text |
Cleaned Pashto article body |
source |
Origin of the example (news outlet / pipeline tag) |
prompt |
Instruction-style prompt derived from the article |
completion |
Expected model output/completion |
instruction |
(JSONL) Instruction text for instruction-tuning |
input |
(JSONL) Optional input/context paired with the instruction |
output |
(JSONL) Target response |
Splits
train: 25,785 examplesvalidation: 2,865 examplesfull: 28,650 examples (union of train + validation)
Accessing the Data
Files are tracked with Git LFS. After cloning, run git lfs pull in the repository to download the actual CSV/JSONL payloads.
Cleaning & Normalisation
- Dropped rows with empty title/text
- Removed duplicate content hashes
- Normalised whitespace and Unicode (NFKC)
- Filtered samples shorter than 10 characters
- Generated aligned prompts, completions, and instruction templates
Intended Uses
- Fine-tuning Pashto T5/mT5 style models
- Instruction-tuning chat assistants for Pashto
- Building evaluation sets for Pashto summarisation and QA
Limitations
- Dominated by news-domain writing; colloquial data is limited
- Automatically generated prompts/completions may include occasional artefacts—consider manual review before deployment
- Despite cleaning, residual duplicated facts may remain due to mirrored reporting across sources
Citation
@misc{tasal2025_zamai_pashto_cleaned,
title = {ZamAI Pashto Dataset (Cleaned)},
author = {Yaqoob Tasal and the ZamAI Team},
year = {2025},
howpublished = {\url{https://huggingface.co/datasets/tasal9/ZamAI-Pashto-Dataset-Cleaned}}
}
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