Datasets:
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Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
English: string
Zomi: string
Explanation: string
Tags: string
english: null
zomi: null
source: null
domain: null
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 713
to
{'english': Value('string'), 'zomi': Value('string'), 'source': Value('string'), 'domain': Value('string')}
because column names don't match
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 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2431, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1984, in _iter_arrow
pa_table = cast_table_to_features(pa_table, self.features)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2192, in cast_table_to_features
raise CastError(
datasets.table.CastError: Couldn't cast
English: string
Zomi: string
Explanation: string
Tags: string
english: null
zomi: null
source: null
domain: null
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 713
to
{'english': Value('string'), 'zomi': Value('string'), 'source': Value('string'), 'domain': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
π Table of Contents
- Project Overview & Mission
- Dataset Statistics & Analytics
- The Zomi AI Architecture
- Linguistic Profile: Understanding Zomi
- Advanced Usage Guide (Python/API)
- Model Benchmarks & Performance
- Contribution & Roadmap
- Data Governance, Ethics & License
- Citation
π Project Overview & Mission
The Zomi Language (ISO 639-3: ctd / zom) is the lingua franca of the Zomi people across the highlands of Myanmar, India (Manipur/Mizoram), and Bangladesh. Despite a vibrant literary history and millions of speakers, it remains "Low-Resource" in the global digital ecosystem.
The Zomi-English Parallel Intelligence Corpus (ZEPIC) is the world's first open-source, machine-readable dataset designed specifically for Large Language Model (LLM) fine-tuning. It moves beyond simple dictionary matching to capture semantic context, idiomatic expressions, and syntactic alignment.
Core Objectives
- Digital Sovereignty: Owning our data to prevent digital extinction and ensuring the Zomi identity thrives in the AI era.
- Educational Access: Enabling instant translation of global knowledge (Science, Medicine, Law) into Zomi.
- Cultural Archiving: Preserving oral history and literature through advanced text generation.
π Dataset Statistics & Analytics
We employ rigorous data cleaning (deduplication, length-ratio filtering) to ensure high-quality training signals.
| Metric | Value | Details |
|---|---|---|
| Total Sentence Pairs | 15,000+ | Validated English-Zomi bitexts. |
| Token Count (En) | ~250,000 | English Source Tokens. |
| Token Count (Zomi) | ~240,000 | Zomi Target Tokens (Agglutinative). |
| Vocabulary Size | 28,400 | Unique Zomi word forms. |
| Avg. Sentence Length | 14.2 Words | Ideal for Transformer context windows. |
| Dialect Standard | Zomi (Standard) | Based on the Tedim literary standard. |
Domain Distribution
pie title Source Domain Distribution
"General Conversation" : 40
"Religious/Theological" : 30
"News & Media" : 15
"Educational/Science" : 10
"Legal/Formal" : 5
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