datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Nepali-HealthChatneptun.scraper
Data in this dataset
Docker & NPM
Scraped using crawl4ai.
The NPM and Docker data was scraped from docs.docker.com and docs.npmjs.com and processed using GPT-4 resulting in docker_documentation.jsonl and npm_documentation.jsonl.
The file training-data-v1.jsonl also includes Titanium, dockerNLcommands and docker_ps.
GitHub
Scraped using firecrawl.
The GitHub data was scraped from docs.github.com/en using firecrawl.A few pages might be missing in the… See the full description on the dataset page: https://huggingface.co/datasets/neptun-org/neptun.scraper.nepal-section-wise-act-datasets
Nepal Section-wise Act Datasets
Dataset Description
This dataset contains section-wise legal acts and laws of Nepal, organized for easy access and analysis. It is designed to support legal research, natural language processing (NLP) tasks, and the development of legal tech applications in Nepal.
Note: This dataset is released for research purposes only. Any other unwanted use can lead to the violation of the intended terms of use and may result in legal action or… See the full description on the dataset page: https://huggingface.co/datasets/ranjitraut/nepal-section-wise-act-datasets.nepali-recipes-qwen-processed
Nepali Recipes for Qwen Fine-tuning
Dataset Description
This dataset contains 1227 Nepali recipes formatted for fine-tuning Qwen models using ChatML format.
Train Split: 900 recipes
Test Split: 327 recipes
Language: Nepali (ne)
Format: Qwen ChatML
Base Model: Qwen/Qwen2-1.5B
Dataset Structure
Data Fields
text: Full ChatML formatted prompt with answer (for training)
test_text: ChatML prompt without answer (for inference)
name: Recipe name in Nepali… See the full description on the dataset page: https://huggingface.co/datasets/sijanpaudel/nepali-recipes-qwen-processed.nepali-qa-9k
Nepali-Qa-9k
nepali-qa-9k is a synthetic Nepali question-answer pairs designed for training and evaluating retrieval models, embedding models, rerankers, and FAQ-style search systems.
Each example consists of a realistic user question, a concise helpful answer, and a domain/category label. The questions are written in natural Nepali and are designed to resemble common real-world queries that users might ask in FAQ pages, help centers, customer-support chatbots, search interfaces, or… See the full description on the dataset page: https://huggingface.co/datasets/jangedoo/nepali-qa-9k.Legal_domain_ocr_extracted_Nepali_sft_dataset
Nepali Legal SFT Dataset — Software Development & Operation Committee Order, 2083
Dataset Summary
This dataset contains 31 single-turn instruction/response pairs in Nepali (Devanagari script), derived from a single Government of Nepal legal instrument:
सफ्टवेयर विकास तथा सञ्चालन समिति (गठन) आदेश, २०८३
(Software Development and Operation Committee (Formation) Order, 2083)
The order was issued by the Government of Nepal under Section 3 of the विकास समिति ऐन, २०१३… See the full description on the dataset page: https://huggingface.co/datasets/Somtharu181coder/Legal_domain_ocr_extracted_Nepali_sft_dataset.nepal-constitution-dataset
Nepal Constitution Dataset
Dataset Description
This dataset contains the Constitution of Nepal (२०७२), organized section-wise for easy access, analysis, and use in NLP and legal tech applications. It is designed to support legal research, educational purposes, and the development of AI-driven tools for the Nepali legal system.
Note: This dataset is released for research purposes only. Any other unwanted use can lead to the violation of the intended terms of use… See the full description on the dataset page: https://huggingface.co/datasets/ranjitraut/nepal-constitution-dataset.nepali-bench
NepaliBench 🏔️
A rigorous evaluation benchmark for Nepali language models.
Why this exists
There is no standard, publicly reproducible benchmark for evaluating
Nepali LLMs. This dataset was created after a systematic evaluation of
himalaya-ai's NanochatGPT and Gemma fine-tune revealed that models
claiming Nepali capability had no shared evaluation standard to measure
against.
Dataset
100 carefully curated evaluation examples across 8 categories:… See the full description on the dataset page: https://huggingface.co/datasets/premmm/nepali-bench.nepal_civilcode_en
Nepal Civil Code Instruct and Response Dataset (English)
Overview
The chhatramani/nepal_civilcode_en dataset contains instruction-response pairs in English, derived from the Nepal Civil Code (Muluki Devani Samhita, 2074 BS), designed for fine-tuning instruction-based large language models (LLMs) such as LLaMA, GPT, or similar models. Each entry includes a prompt (instruction), an optional input field (currently empty), and a detailed response based on the legal provisions… See the full description on the dataset page: https://huggingface.co/datasets/chhatramani/nepal_civilcode_en.Nepali-Datasets-Reasoning-Grounding-V1Copyright 2026 Sandesh Bastola
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language… See the full description on the dataset page: https://huggingface.co/datasets/Matrix-Man-Lab/Nepali-Datasets-Reasoning-Grounding-V1.Nepali_law_articles_corpus
Nepal Legal & Government Education Corpus
Dataset Summary
This dataset is a collection of 868 explanatory legal and government-procedure
articles scraped from 11 trusted Nepalese sources — legal blogs,
law firm publications, government portals, and legal aid / human-rights
organizations. It was built as part of NyayaLM, a bilingual (Nepali-English)
legal foundation language model for Nepal, where it serves as one of the
general-education corpora used to ground the… See the full description on the dataset page: https://huggingface.co/datasets/gahann/Nepali_law_articles_corpus.nepali-summarization-datasetThis dataset was intended to to be used for finetuning the nepali text summerization task.
Feel free to contribute to this readme to add any information
Driving_License_Nepali_MultimodalThis dataset is curated as part of the Cohere4AI project called "Multimodal-Multilingual Exam Collection".
Nepali-Health-QA
Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More… See the full description on the dataset page: https://huggingface.co/datasets/Chhabi/Nepali-Health-QA.nepal_5_law_RAG_QA
Nepal Legal QA — Bilingual RAG Fine-Tuning Dataset
A bilingual (English + Nepali) question-answering dataset built from 9 primary Nepali law texts for fine-tuning Small Language Models (SLMs) on Retrieval-Augmented Generation (RAG) tasks in the Nepal legal domain. Every answer is grounded in retrieved legal text with precise section/article citations.
Dataset Summary
Split
Total QA Pairs
Failed Chunks
Train
4,288
0
Test
550
0
Total
4,838
0
Both splits… See the full description on the dataset page: https://huggingface.co/datasets/chhatramani/nepal_5_law_RAG_QA.textbooks-qa-nepali
Textbook Question-Answering Dataset (Nepali)
This repository contains ShareGPT-style conversations generated by the Textbook QA agentic pipeline.
Splits
train: validated conversations with non-empty question, answer, and rephrased_text.
Usage
from datasets import load_dataset
ds = load_dataset("dineshkarki/textbooks-qa-nepali")
train = ds["train"]
Schema
train: each row contains:
id: unique string
conversations: list of 2 messages: human and gpt… See the full description on the dataset page: https://huggingface.co/datasets/dineshkarki/textbooks-qa-nepali.NEPABench
NEPABench
A comprehensive benchmark suite for evaluating large language models on tasks related to the National Environmental Policy Act (NEPA) environmental review and permitting process.
Citation
If you use NEPABench, please cite:
@misc{acharya2026nepabench,
author={Anurag Acharya and Rounak Meyur and Sai Koneru and Kaustav Bhattacharjee and Bishal Lakha and Alexander C. Buchko and Reilly P. Raab and Hung Phan and Koby Hayashi and Dan Nally and Mike Parker and Sai… See the full description on the dataset page: https://huggingface.co/datasets/PNNL/NEPABench.textbook-qa-nepali-reasoning
Textbook Question-Answering Dataset (Nepali)
This repository contains ShareGPT-style conversations generated by the Textbook QA agentic pipeline.
Splits
train: validated conversations with non-empty question, answer, and rephrased_text.
Usage
from datasets import load_dataset
ds = load_dataset("dineshkarki/textbook-qa-nepali-reasoning")
train = ds["train"]
Schema
train: each row contains:
id: unique string
conversations: list of N messages (N ≥… See the full description on the dataset page: https://huggingface.co/datasets/dineshkarki/textbook-qa-nepali-reasoning.Nepali_Legal_QA
Nepali Legal QA Dataset
Dataset Description
This dataset contains question-answer pairs in Nepali language related to various legal documents and laws of Nepal. The dataset is designed to facilitate research and development in natural language processing applications for the Nepali legal domain, including legal question answering, information retrieval, and legal document analysis.
Dataset Structure
The dataset is organized in a tabular format with the… See the full description on the dataset page: https://huggingface.co/datasets/Bhugol/Nepali_Legal_QA.xquad-nepali
XQuAD-NP: Nepali Translation of XQuAD
Overview
XQuAD-NP is a Nepali translation of the XQuAD dataset, a multilingual benchmark for evaluating question-answering models. The dataset consists of Nepali translations of the original English passages, questions, and answers from the XQuAD dataset. This resource is useful for benchmarking and improving the performance of machine learning models on extractive question-answering tasks in Nepali.
Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/Yunika/xquad-nepali.Nepali-QA
Dataset Summary
This dataset comprises 266 Nepali question-answer (QA) pairs, created using the Belebele dataset and the Haystack annotation tool. It serves as a benchmark for evaluating QA models against human-curated data, providing insights into performance variations due to distribution shifts from standard SQuAD datasets to human-annotated datasets.
Dataset Creation
Source Data
Original Source: Belebele dataset, which spans 122 language variants… See the full description on the dataset page: https://huggingface.co/datasets/Yunika/Nepali-QA.nepal-legal-qa-benchmark_v1
🇳🇵 Nepal Legal QA Benchmark V1
A grounded, citation-rich Question-Answer benchmark dataset covering 9 foundational Nepali law texts — in both English and Nepali (Devanagari) — for evaluating and fine-tuning legal AI systems.
📖 Dataset Description
Nepal Legal QA Benchmark is a synthetic-but-grounded dataset of 4,328 instruction-following QA pairs generated from the full text of Nepal's most important statutes. Every answer is grounded exclusively in the source legal… See the full description on the dataset page: https://huggingface.co/datasets/chhatramani/nepal-legal-qa-benchmark_v1.nepali-Psychology-domain-behaviour-diversity-complexity-sft-dataset
🧠 Nepali Psychology Question Dataset — 2,000 Samples
📌 Overview
The Nepali Psychology Question Dataset is a specialized Nepali-language dataset containing 2,000 psychology-related question-answer records designed for Natural Language Processing (NLP), Large Language Models (LLMs), Small Language Models (SLMs), Supervised Fine-Tuning (SFT), Question Answering (QA), instruction tuning, educational AI, and psychology-domain research.
The dataset is designed with a… See the full description on the dataset page: https://huggingface.co/datasets/sabin1234/nepali-Psychology-domain-behaviour-diversity-complexity-sft-dataset.Nepali_Legal_QA
Nepali Legal QA Dataset
Dataset Description
This dataset contains question-answer pairs in Nepali language related to various legal documents and laws of Nepal. The dataset is designed to facilitate research and development in natural language processing applications for the Nepali legal domain, including legal question answering, information retrieval, and legal document analysis.
Dataset Structure
The dataset is organized in a tabular format with the… See the full description on the dataset page: https://huggingface.co/datasets/chhatramani/Nepali_Legal_QA.nepal_civil_law_QA_v2
📚 Nepal Civil Law QA Dataset v2
A high-quality, instruction-style QA dataset generated from the Nepal Civil Code 2074 (नेपालको देवानी संहिता २०७४), designed for fine-tuning and evaluating legal-domain LLMs focused on Nepal.
🔗 Dataset hosted on Hugging Face: chhatramani/nepal_civil_law_QA_v2
📌 Dataset Overview
This dataset was created using synthetic QA generation from official legal documents of Nepal, primarily focusing on civil law. Using a combination of… See the full description on the dataset page: https://huggingface.co/datasets/chhatramani/nepal_civil_law_QA_v2.textbook-qa-nepali-multiturn
Textbook Question-Answering Dataset (Nepali)
This repository contains ShareGPT-style conversations generated by the Textbook QA agentic pipeline.
Splits
train: validated conversations with non-empty question, answer, and rephrased_text.
Usage
from datasets import load_dataset
ds = load_dataset("dineshkarki/textbook-qa-nepali-multiturn")
train = ds["train"]
Schema
train: each row contains:
id: unique string
conversations: list of N messages (N ≥… See the full description on the dataset page: https://huggingface.co/datasets/dineshkarki/textbook-qa-nepali-multiturn.Multilingual-Nepali-Customer-Care-Services-DatasetCustomer-Care-Services-Dataset-in-Nepalinepali_muluki_dewani_QA_v1
Nepali Muliki Dewani Samhita 2074 Q&A Dataset
This dataset contains Question-Answer (Q&A) pairs derived from the Nepal Civil Code 2074 (Muluki Devani Samhita Ain, 2074). It is designed to facilitate the development and fine-tuning of Large Language Models (LLMs) for understanding and generating responses related to Nepali Civil Law.
Dataset Description
The dataset was synthetically generated using the Google Gemini 2.0 Flash model, processing the full text of the Nepal… See the full description on the dataset page: https://huggingface.co/datasets/chhatramani/nepali_muluki_dewani_QA_v1.nepali-query-passage-hard-negatives-10k