datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
adaption-urdu-edu-cultural-reasoning
This dataset is a remastered version prepared using Adaption's Adaptive Data platform.
adaption-urdu_edu_cultural_reasoning
This dataset contains a mixed collection of question-answer pairs and linguistic tasks presented in both English and Urdu. The content spans multiple domains including history, biology, geography, and Urdu literature, featuring multiple-choice questions, translation exercises, and poetic composition prompts. Samples include historical treaty analysis… See the full description on the dataset page: https://huggingface.co/datasets/abdullah693/adaption-urdu-edu-cultural-reasoning.urdu-emergency-calls
Urdu Emergency Call Conversations Dataset (Pakistan)
Overview
This dataset contains 5,000 curated Urdu emergency call conversation samples from the Pakistan region, designed to support training and evaluation of Urdu Large Language Models (LLMs) for emergency response, command centers, and interpreter-style systems.
The conversations simulate real-world emergency scenarios such as:
Floods
Medical emergencies
Accidents
Crimes
Natural disasters
Public safety… See the full description on the dataset page: https://huggingface.co/datasets/abeeranajam31/urdu-emergency-calls.roman-urdu-qwen25-3b-blindspot
Roman Urdu / code-switch blind spot (Qwen2.5-3B-Instruct)
Hand-built eval: 8 Pakistani situations x 3 surfaces (English, formal Urdu, Roman Urdu).
Model: Qwen/Qwen2.5-3B-Instruct. Greedy decoding, 4-bit, Colab T4.
Evaluation
condition
pass
n
rate
english
7
8
0.88
formal_urdu
3
8
0.38
roman_urdu
1
8
0.12
Files: prompts.jsonl, outputs.jsonl, judged.jsonl, scores.json
Roman Urdu traces:
01_ro: NADRA described as a motor-vehicle department
02_ro:… See the full description on the dataset page: https://huggingface.co/datasets/Ashar086/roman-urdu-qwen25-3b-blindspot.roman-urdu-alpaca-qa-mix
Dataset Card for Roman Urdu + Alpaca QA Mix
This dataset is intended to support fine-tuning and evaluation of language models that understand and respond to Roman Urdu and English instructions. It consists of 1,022 records in total:
500 examples in Roman Urdu generated from high-quality Urdu sources and transliterated using the ChatGPT API.
500 examples in English randomly sampled from the Stanford Alpaca dataset.
The dataset follows the same format as Alpaca-style instruction… See the full description on the dataset page: https://huggingface.co/datasets/Redgerd/roman-urdu-alpaca-qa-mix.urdu-emergency-calls
Urdu Emergency Call Conversations Dataset (Pakistan)
Overview
This dataset contains 5,000 curated Urdu emergency call conversation samples from the Pakistan region, designed to support training and evaluation of Urdu Large Language Models (LLMs) for emergency response, command centers, and interpreter-style systems.
The conversations simulate real-world emergency scenarios such as:
Floods
Medical emergencies
Accidents
Crimes
Natural disasters
Public safety incidents
The… See the full description on the dataset page: https://huggingface.co/datasets/hamza-amin/urdu-emergency-calls.Urdu-Training-for-NLP
Urdu Instruction Dataset for NLP
A manually curated dataset of 578 Urdu instruction-response
pairs for fine-tuning language models on Urdu NLP tasks.
Dataset Description
This dataset was created to address the lack of
instruction-tuning data for Urdu, a low-resource language
spoken by over 230 million people. All examples were written
and verified by a native Urdu speaker.
Dataset Structure
Each example contains a conversation with a user… See the full description on the dataset page: https://huggingface.co/datasets/Almanships/Urdu-Training-for-NLP.UrduReason-Eval
UrduReason-Eval
A Standardized Urdu Reasoning Evaluation Benchmark for Large Language Models
UrduReason-Eval is a high-difficulty, evaluation-only reasoning benchmark designed specifically to measure multi-step reasoning capabilities in Urdu-language LLMs.
It is one of the few publicly available datasets that jointly evaluates linguistic understanding and formal reasoning in Urdu, a low-resource language spoken by over 230 million people.
If you are evaluating Urdu LLM reasoning… See the full description on the dataset page: https://huggingface.co/datasets/HaseebAsif/UrduReason-Eval.