datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
bodo-legal-question-answering-ai4bharat
Bodo Legal Question Answering Dataset
Overview
This dataset is a Bodo-language legal Question Answering (QA) resource
created for research in low-resource Natural Language Processing (NLP)
and legal language processing.
The supplied source files contain legal judgment contexts together with
multiple questions and answers. For Hugging Face compatibility and
question-answering model training, each question-answer pair has been
flattened into a separate JSONL example… See the full description on the dataset page: https://huggingface.co/datasets/Mwnthai/bodo-legal-question-answering-ai4bharat.bodo-monolingual-dataset# First Install datasets library
pip install datasets
from datasets import load_dataset
train = load_dataset("alayaran/bodo-monolingual-dataset", "unshuffled_deduplicated_no", split="train")
test = load_dataset("alayaran/bodo-monolingual-dataset", "unshuffled_deduplicated_no", split="test")
# print the first five entries from the dataset array of trai and test set
print(train['text'][:5])
["मदि सरकारा जारिमिनारि हाबाफारि मावफूंदों , 1 कौटि नख'राव दैनि कानेक्सन होबाय",
"दिल्ली / जयपुर… See the full description on the dataset page: https://huggingface.co/datasets/alayaran/bodo-monolingual-dataset.bodo_english_parallelBodo and English Parallel Sentences
2 languages, 3 bitexts
;) @alayaranDual-Use-Goodsbodo-legal-question-answering-iiith
Bodo Legal Question Answering Dataset — IIITH Translation
Overview
A Bodo-language legal Question Answering (QA) resource derived from
English legal judgments. Each example contains a judgment context, a
question, and its corresponding answer.
Data Provenance
Original Legal Source
The underlying English legal judgments were extracted from the publicly
accessible Gauhati High Court judgment repository:… See the full description on the dataset page: https://huggingface.co/datasets/Mwnthai/bodo-legal-question-answering-iiith.bodo-news-headlinebodo-legal-judgment-summarization
Bodo Legal Judgment Summarization Dataset
Overview
This dataset contains Bodo-language legal judgments paired with their
corresponding summaries. It is intended for research on automatic legal
text summarization, low-resource NLP, and Bodo language modeling.
Dataset Structure
Each example contains:
id: Document identifier corresponding to the original TXT filenames.
language: Language of the document (Bodo).
domain: Domain (Legal).
judgment: Full… See the full description on the dataset page: https://huggingface.co/datasets/Mwnthai/bodo-legal-judgment-summarization.ICON26-COILD-INDIC-MT-Assamese-Bodo
COILD-INDIC-MT 2026 — Assamese–Bodo Dataset
This dataset is provided for the COILD-INDIC-MT 2026 Shared Task, co-located with ICON 2026.
The shared task aims to foster research and innovation in Natural Language Processing (NLP) for Indian Languages.
This repository contains data specifically for the:
Assamese ↔ Bodo
language pair.
🔐 Access to the Dataset
This is a restricted and gated dataset.
Access is available only to authorized participants of the… See the full description on the dataset page: https://huggingface.co/datasets/ainlpml-iitp/ICON26-COILD-INDIC-MT-Assamese-Bodo.bodo_c4_0001_dedupedBodo language synthetic pretraining data, original source language is english.
Original dataset details
wget https://huggingface.co/datasets/allenai/c4/resolve/main/en/c4-train.00000-of-01024.json.gz
gunzip c4-train.00000-of-01024.json.gz
Translation parameters:
FORWARD_MODEL_NAME = "prajdabre/rotary-indictrans2-en-indic-1B"
BATCH_SIZE = 256
NUM_WORKERS = 8
MAX_SEQ_LENGTH = 256
NUM_BEAMS = 1
bodo
Speed-Tb Phase 1 Bodo Narration
Dataset Description
The Bodo Speech Dataset, developed as part of the
Speech Datasets and Models for Tibeto-Burman Languages (Project SpeeD-TB),
funded under Mission Bhashini, is a transcribed speech corpus of the language.
The full dataset comprises over 200 hours of high-quality audio recordings paired with accurate transcriptions in both IPA and Roman script, making it
** one of the largest speech resources for the language**… See the full description on the dataset page: https://huggingface.co/datasets/speed-tb/bodo.bodo_english_parallel_validBodo and English Parallel Sentences
2 languages, 3 bitexts
;) @alayaranbodo-wordsbodo_english_parallel_testBodo and English Parallel Sentences
2 languages, 3 bitexts
;) @alayaranbodo-pos-conllThe shared task of CoNLL-2003 concerns language-independent named entity recognition. We will concentrate on
four types of named entities: persons, locations, organizations and names of miscellaneous entities that do
not belong to the previous three groups.
The CoNLL-2003 shared task data files contain four columns separated by a single space. Each word has been put on
a separate line and there is an empty line after each sentence. The first item on each line is a word, the second
a part-of-speech (POS) tag, the third a syntactic chunk tag and the fourth the named entity tag. The chunk tags
and the named entity tags have the format I-TYPE which means that the word is inside a phrase of type TYPE. Only
if two phrases of the same type immediately follow each other, the first word of the second phrase will have tag
B-TYPE to show that it starts a new phrase. A word with tag O is not part of a phrase. Note the dataset uses IOB2
tagging scheme, whereas the original dataset uses IOB1.
For more details see https://www.clips.uantwerpen.be/conll2003/ner/ and https://www.aclweb.org/anthology/W03-0419BodoASR-Bodo_5hrsbodo_cardiology_risk_reasoning_v1.jsonbodo_cardiology_reasoning_v2.jsonbodo_neuro_critical_reasoning_v1.jsonbodo_obstetrics_critical_reasoning_v1.jsonbodo_endocrine_reasoning_v1.jsonbodo_emergency_critical_reasoning_v2.jsonbodo_emergency_critical_reasoning_v3.jsonbodo_icu_multisystem_critical_reasoning_v1.jsonbodo_infectious_critical_reasoning_v1.json