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Nepali Datasets Collection

A comprehensive, organized collection of 200+ Nepali datasets across NLP, Computer Vision, Speech, OCR, and more for AI/ML research and development.

Table of Contents

  1. LLM Development Resources
  2. Benchmarks and Standards
  3. Text Corpora
  4. NLP Datasets
  5. Translation and Parallel Data
  6. Speech and Audio Datasets
  7. Computer Vision Datasets
  8. OCR and Handwriting Datasets
  9. Lexicons and Linguistic Resources
  10. Pre-trained Models and Embeddings
  11. Tools and Frameworks
  12. Research Papers
  13. Open Data and Government Resources
  14. Additional Resources
  15. Dataset Search Guide

LLM Development Resources

Pre-training Corpora

Ultra-Large (Greater Than 1GB)

Dataset Size Source Link
Nepali-Text-Corpus (IRIISNEPAL) 6.4M articles, 10.1 GB 99 news websites HF
OSCAR Corpus Nepali 3.8 GB, 100M+ sentences Common Crawl Kaggle
CC100-Nepali 200GB uncompressed Common Crawl 2019 MetaText
Large Scale Nepali Text Corpus Large-scale General IEEE Dataport
Boredoom17 Nepali Corpus - General HF
Gold Standard Nepali Raw Text Corpus - Raw text LDCIL
Language Resources for Nepal Multiple datasets Aggregated collection language-resources-nepal.github.io
OpenWiseyak-0.1-Pretraining - Wiseyak HF
Wiseyak-SFT-Mixed-ne-en - Wiseyak HF
Ministry of Finance Nepal Corpus 2015-2024 (Fiscal Years 2072/73-2080/81) Government reports HF: lilgoose777/mof-nepal-nepali
Nepali LLM Datasets - Aggregated HF: Aananda-giri/nepali_llm_datasets
NaBI Corpus - - HF: Utkarsha666/NaBI
nepali-pretrain-corpus (HimalayaAI) 4.29 GB kaggle:hsebarp/oscar-corpus-nepali HF
nepali-sft-dataset (HimalayaAI) 3.8 GB dineshkarki/textbooks-qa-nepali HF
nepali-news-corpus (HimalayaAI) 1.84 GB newsportal HF

Large Curated (100MB-1GB)

Dataset Size Description Link
Nepali News Dataset 6,800+ articles With metadata Kaggle
Nepali Wikipedia Articles 39,000+ articles Wikipedia dump Kaggle
np20ng (20 Newsgroup) 200,000+ documents 20 categories HF
Nepali News Dataset (Large) 25,000+ articles 10+ categories Kaggle
Ashok Pant Nepali News Dataset 25,000+ articles 10+ categories Kaggle: ashokpant/nepali-news-dataset-large
Nagarik News Corpus - News GitHub
Setopati News Corpus - News GitHub
Spandyie Nepali News Dataset Large collection Baahrakhari and other sources, cleaned category labels HF: spandyie/nepali-news-dataset

Specialized

Dataset Size Domain Link
Digitized Nepali Textbooks OCR'd textbooks Formal register HF
Nepali Lyrics Dataset 5,000+ lyrics Music domain Kaggle
65K Nepali Sentences 65,000 sentences General GitHub
350K Nepali Sentences 350,000 sentences General GitHub
Laxmi Prasad Devkota Poems 119,161 characters Literary GitHub
Nepali Ukhaan Tukka (Proverbs) - Proverbs GitHub
Nepali Ngram - N-grams GitHub
Nepali Chat Corpus - Chat/conversational GitHub
English News Corpus (Nepal) - English news about Nepal GitHub
Nepal Earthquake Tweets - Social media (disaster) CrisisNLP
Nepali Sentences Corpus - General Kaggle: sparshrestha/nepali-sentences-corpus
Nepali Election Results Historical - Government Kaggle: dimanjung/nepali-election-results-historical
Gender Based Violence in Nepal 2019-2026 - Social Kaggle: aneeshmhj/gender-based-violence-in-nepal-2019-2026
Nepal Earthquake Seismicity Dataset 1990-2026 Geological Kaggle: amansinghnp/nepal-earthquake-seismicity-dataset-1990-2026
Nepal Multi-District Weather Dataset 2020-2025 Meteorological Kaggle: dipeshthapa1/nepal-multi-district-weather-dataset-2020-2025
House Price Dataset Nepal - Real Estate Kaggle: nishanpokh/house-price-dataset-nepal
Nepal Trekking Dataset - Tourism Kaggle: bibekrai44/nepal-treking-dataset
Nepali Surname/Caste/Ethnicity Datasets - Demographic Kaggle: nayansubedi1/nepali-surname-caste-ethnicity-datasets

Fine-tuning Datasets

Text Classification

Dataset Size Categories Link
16NepaliNews Corpus ~14,364 documents 16 categories GitHub
iNLTK Nepali News Dataset 8,000+ articles 5 categories Kaggle
Nepali News Dataset 6,800+ articles With metadata Kaggle
Nepali News Classification Dataset - - Google Drive
Nepali News Datasets (Small) 3,000+ articles - Kaggle
Prasta Dataset - Question type classification Kaggle
Nepali Factoid Questions Intent Classified 500+ samples Intent detection Kaggle
AshokNepal Nepali News Classification - News categories Kaggle: ashoknepal/nepali-news-classification

Question Answering

Dataset Size Type Domain Link
Nepali Health Q and A Corpus 3,000+ Q and A pairs - Medical Kaggle
Pregnancy Related Q and A 1,500+ pairs - Maternal health Kaggle
Nepali Health Forum Corpus 2,500+ Q and A With user interactions Medical Kaggle
Nepali QA Dataset (Yunika) 266 pairs Extractive - HF
Nepali Driving License Test - Question Answering - HF: sharad461/nepali-driving-license-test

Summarization

Dataset Size Type Link
Nepali News Article with Summary 286,000+ pairs Headline generation Kaggle
Nepali text summarization 1,000+ pairs Abstractive Kaggle
Nepali Abstractive Summarization Corpus 286k article-title pairs Abstractive Google Drive
Sentence Compression Nepali 5,000+ pairs Extractive Kaggle
Policy Documents and Summaries 500+ documents Domain-specific Kaggle
Sanjeev Bhandari Nepali Summarization - Abstractive HF: sanjeev-bhandari01/nepali-summarization-dataset

Named Entity Recognition (NER)

Dataset Size Entity Types Link
EverestNER 50,000+ sentences 8 types Kaggle
DanfeNER 25,000+ sentences Geographical and cultural Kaggle
Nepali NER (Ebiquity v2) - PER, ORG, LOC GitHub
Nepali NER Dataset (dadelani) - Multi-token entities GitHub
Nepali Offensive Language NER and Sentiment 5,000+ samples Dual annotations Kaggle

Sentiment Analysis

Dataset Size Type Domain Link
NepaliSentiment - With preprocessing and baselines - GitHub
Nepali Sentiment Analysis - Binary classification - Kaggle
Nepali Language Sentiment Analysis - Movie Reviews 2,500+ reviews Star ratings Film Kaggle
Nepali Luxury Hotel Reviews 4,000+ reviews Aspect-based Hotel Kaggle
XLSum-Nepali - Summarization + sentiment - HF
Nepali Data Set for Sentiment Analysis - - - Mahesha
Sentiment Analysis in Nepali - - - GitHub
SentimentAnalysis - - - GitHub
Oya163 Nepali Sentiment Analysis - Aspect-based abusive sentiment Social media GitHub: oya163/nepali-sentiment-analysis
Nepali Fake News Dataset v1 8,838 samples Binary classification Synthetic (LLM-generated) HF: chhatramani/nepali-fake-news-dataset-v1

Hate Speech and Offensive Language

Dataset Size Type Platform Link
Nepali Hate Speech Collection 5,000+ samples Annotated Social media Kaggle
Nepali Offensive Language Detection - Detection tooling - GitHub
Nepali Abusive Language NER and Sentiment - Multi-task Abusive text Kaggle
NepCov19Tweets 10,000+ tweets Emotion labels Twitter Kaggle
Mpox Instagram Sentiment and Hate Analysis 3,000+ posts Dual sentiment + hate labels Instagram Kaggle
Nepali Financial News Dataset - Domain-specific - Kaggle: anujbhattrai/the-nepali-financial-news-dataset

Translation and Parallel Data

Large-Scale Parallel Corpora

Dataset Size Language Pair Link
English-Nepali Parallel Corpus (Kathmandu University) 1,800,000 pairs EN-NE ELRA W0077
Kathmandu University English-Nepali Corpus 1.8M pairs EN-NE AI4Bharat
English-Nepali Translation Instruction Dataset - EN-NE HF: ashokpoudel/English-Nepali-Translation-Instruction-Dataset

Medium-Scale Corpora

Dataset Size Language Pair Link
Nepali-English language pair 40,000+ pairs EN-NE GitHub
Hindi-Nepali Parallel Corpus (Noisy) 500,000+ pairs HI-NE Kaggle
Hindi-Nepali Evaluation Corpus (Clean) 50,000+ pairs HI-NE Kaggle
Urdu-Nepali Parallel Corpus 100,000+ pairs UR-NE Kaggle
English to Nepali Translation - EN-NE GitHub
Nepali-English Translation Dataset - EN-NE GitHub
Nepali Translation Parallel Corpus - EN-NE Google Drive
English-Nepali Translated Strings (TDIL) - UI/software localization TDIL-DC

Multilingual and Specialized

Dataset Size Languages Domain Link
Trilingual Hindi-English-Nepali 200,000+ triples HI-EN-NE - Kaggle
English-Nepali Translation (HF) - EN-NE Instruction-tuned HF
Bidirectional EN-NE MT (Legal) 125,000 sentences EN-NE Legal ACL Paper
CLE Parallel Corpus - EN-NE-UR - AI4Bharat

Historical and Shared Tasks

Dataset Event Link
WMT19 Parallel Corpus Shared task statmt.org
FLORES 101 Dataset Multilingual benchmark GitHub

Instruction Tuning

Dataset Languages Type Link
Bactrian-X 50+ languages (includes Nepali) Instruction tuning HF
Aya Dataset 101 languages (includes Nepali) Instruction tuning HF

Benchmarks and Standards

Comprehensive evaluation frameworks and shared tasks for Nepali NLP.

Benchmark Tasks Link
NLUE (Nepali Language Understanding Evaluation) 9 classification + 3 structural prediction tasks (sentiment, hate speech, toxicity, QA, NER) arXiv: 2411.19244
Nep-gLUE Benchmark Official Nepali GLUE-style benchmark (7 NLU tasks) Limited direct access; see NLUE for comprehensive alternatives
FLORES-101 Evaluation Benchmark Machine translation evaluation across 101 languages including Nepali GitHub: facebookresearch/flores
IndicBench Benchmark for 11 Indic languages including Nepali (13 tasks) New 2025 addition
SemEval 2026 Task 9 Polarization type classification with Nepali data Codabench
Google FLEURS Multilingual benchmark including Nepali (101 languages) HF: google/fleurs

Text Corpora

Ultra-Large Corpora (Greater Than 1GB)

Dataset Size Source Link
Nepali-Text-Corpus (IRIISNEPAL) 6.4M articles, 10.1 GB Largest Nepali corpus from 99 news websites HF: IRIISNEPAL/nepali-text-corpus
OSCAR Corpus Nepali 3.8 GB, 100M+ sentences Common Crawl Kaggle: hsebarp/oscar-corpus-nepali
CC100-Nepali Common Crawl 2019 subset, 200GB uncompressed Foundation data for multilingual models MetaText: cc100-nepali
Lamsal (2020) Corpus 12M+ words Professionally compiled Note: Original DOI 404; consider IRIISNEPAL as primary substitute

Large Curated Collections (100MB-1GB)

Dataset Size Description Link
Nepali News Dataset 6,800+ articles with metadata Kaggle: lotusacharya/nepalinewsdataset
Nepali Wikipedia Articles 39,000+ articles from Wikipedia dump Kaggle: disisbig/nepali-wikipedia-articles
np20ng (20 Newsgroup) 200,000+ news documents across 20 categories Adapted from English 20NG HF: Suyogyart/np20ng
Nepali News Dataset (Large) 25,000+ articles across 10+ categories Kaggle: ashokpant/nepali-news-dataset-large
Spandyie Nepali News Dataset Large collection News articles scraped from Baahrakhari and other Nepali news sources, with cleaned category labels HF: spandyie/nepali-news-dataset

Specialized Text Collections

Dataset Size Domain Link
Nepali Unigrams Cleaned (FineWeb) 200k+ unique Nepali words with frequency Kaggle: thenepaliguy/nepali-unigrams-cleaned
Setopati News Dataset 10,000+ articles from Setopati portal News domain-specific Kaggle: living0world/setopati-news-dataset
Nepali Raw Text Data Raw text batches for preprocessing Kaggle: rajanghimire/nepali-raw-text-data-batch1
Nepali Lyrics Dataset 5,000+ song lyrics with metadata Music domain Kaggle: sanjay05kc/nepali-lyrics
Digitized Nepali Textbooks OCR'd school textbooks (formal register) HF: dineshkarki/nepali-textbooks-corpus

NLP Datasets

Classification Datasets

News classification, topic modeling, and text categorization.

Dataset Size Description Link
iNLTK Nepali News Dataset 8,000+ articles across 5 categories Kaggle: disisbig/nepali-news-dataset
16NepaliNews Corpus ~14,364 documents across 16 categories Most comprehensive category coverage GitHub: sndsabin/Nepali-News-Classifier
Nepali News Datasets (Small) 3,000+ articles Good for quick prototyping Kaggle: tejshahi/20nepalinews
Prasta Dataset Question type classification for QA systems Kaggle: sangamthapa/prasta
Nepali Factoid Questions Intent Classified 500+ samples for intent detection Kaggle: sushiltimilsina/nepali-factoid-questions-intent-classified-dataset
AshokNepal Nepali News Classification - News article classification Kaggle: ashoknepal/nepali-news-classification

Named Entity Recognition (NER) Datasets

Annotated datasets for entity recognition (person, organization, location, etc.).

Dataset Size Description Link
EverestNER 50,000+ annotated sentences, 8 entity types Largest NER dataset Kaggle: jeevanchapagain/everestner
DanfeNER 25,000+ sentences covering Nepali geographical and cultural entities Kaggle: jeevanchapagain/danfener
Nepali NER (Ebiquity v2) Benchmark dataset with 3 entity types (PER, ORG, LOC) GitHub: oya163/nepali-ner/data/ebiquity_v2
Nepali NER Dataset (dadelani) Annotated for multi-token entities GitHub: dadelani/nepali-ner
Nepali Offensive Language NER and Sentiment 5,000+ samples with dual annotations (NER + sentiment) Kaggle: merishnasuwal/offensive-language-ner-and-sentiment-analysis-data

Sentiment Analysis and Hate Speech Datasets

Social media, news, and online text with sentiment/toxicity annotations.

Sentiment Analysis

Dataset Size Description Link
NepaliSentiment GitHub corpus with preprocessing and baselines GitHub: rockerritesh/NepaliSentiment
Nepali Sentiment Analysis Binary classification (positive/negative) Kaggle: aayamoza/nepali-sentiment-analysis
Nepali Language Sentiment Analysis - Movie Reviews 2,500+ reviews with star ratings Domain-specific (film) Kaggle: shikharghimire/nepali-language-sentiment-analysis-movie-reviews
Nepali Luxury Hotel Reviews 4,000+ reviews with aspect-based sentiment Hotel domain Kaggle: suprapandey/nepali-luxury-hotel-reviews-2024
XLSum-Nepali Summarization + sentiment HF: sanjeev-bhandari01/XLSum-nepali
Nepali Data Set for Sentiment Analysis - - Mahesha
Sentiment Analysis in Nepali - - GitHub
SentimentAnalysis - - GitHub
Oya163 Nepali Sentiment Analysis - Aspect-based abusive sentiment GitHub: oya163/nepali-sentiment-analysis
Nepali Fake News Dataset v1 8,838 labeled samples Binary classification (real vs fictional) HF: chhatramani/nepali-fake-news-dataset-v1

Hate Speech and Offensive Language

Dataset Size Description Link
Nepali Hate Speech Collection 5,000+ annotated samples from social media Kaggle: mohanbhandari/nepali-hate-speech-collection
Nepali Offensive Language Detection - Detection tooling GitHub: merishnaSuwal/nep-off-langdetect
Nepali Abusive Language NER and Sentiment - Multi-task (NER + sentiment on abusive text) Kaggle: merishnasuwal/offensive-language-ner-and-sentiment-analysis-data
NepCov19Tweets 10,000+ tweets Emotion labels Kaggle: mathew11111/nepcov19tweets
Mpox Instagram Sentiment and Hate Analysis 3,000+ posts Dual sentiment + hate labels Kaggle: thakurnirmalya/mpox-instagram-dataset-sentiment-and-hate-analysis

Question Answering (QA) Datasets

Extractive, generative, and domain-specific QA datasets.

Dataset Size Description Link
Nepali Health Q and A Corpus 3,000+ Q and A pairs from health forums Medical domain Kaggle: thedevastator/nepali-health-q-a-corpus
Pregnancy Related Question Answer 1,500+ pairs Maternal health (specialty medical) Kaggle: poudelsujan03/pregnancy-related-question-answer-nepali-dataset
Nepali Health Forum Corpus 2,500+ Q and A from health forums With user interactions, medical domain Kaggle: rxnach/nepali-health-forum-corpus-questions-and-answers
Nepali QA Dataset (Yunika) 266 extractive QA pairs With passage context, HuggingFace format HF: Yunika/Nepali-QA
Nepali Driving License Test - Question answering HF: sharad461/nepali-driving-license-test

Summarization Datasets

Abstractive and extractive summarization, headline generation.

Dataset Size Description Link
Nepali News Article with Summary 286,000+ news headlines + articles Largest summarization resource (headline generation) Kaggle: adarsh203/nepali-news-article-with-summary
Nepali text summarization 1,000+ document-summary pairs Abstractive task Kaggle: imageinfo/nepali-text-summarization
Nepali Abstractive Summarization Corpus 286k article-title pairs Abstractive Google Drive
Sentence Compression Nepali 5,000+ sentence pairs Text compression (extractive) Kaggle: sbastola73/sentence-compression-nepali
Policy Documents and Summaries 500+ documents Domain-specific (policy) Kaggle: greenspaghetti/policy-documents-and-summaries
Sanjeev Bhandari Nepali Summarization - Abstractive, fine-tuning dataset HF: sanjeev-bhandari01/nepali-summarization-dataset

Translation and Parallel Data

Parallel corpora for machine translation and low-resource language pairs.

Large-Scale Parallel Corpora

Dataset Size Language Pair Link
English-Nepali Parallel Corpus (Kathmandu University) 1,800,000 sentence pairs EN-NE ELRA W0077
Kathmandu University English-Nepali Corpus 1.8M sentence pairs EN-NE AI4Bharat

Medium-Scale Corpora

Dataset Size Language Pair Link
Nepali-English language pair 40,000+ parallel sentence pairs EN-NE GitHub: sharad461/nepali-translator
Hindi-Nepali Parallel Corpus (Noisy) 500,000+ sentence pairs HI-NE Kaggle: thenepaliguy/final-hi-ne
Hindi-Nepali Evaluation Corpus (Clean) 50,000+ high-quality sentence pairs HI-NE Kaggle: thenepaliguy/cleanhindinepali
Urdu-Nepali Parallel Corpus 100,000+ sentence pairs UR-NE Kaggle: rtatman/urdunepali-parallel-corpus
English to Nepali Translation - EN-NE GitHub: arunism/English-to-Nepali-Language-Translation/tree/master/data
Nepali-English Translation Dataset - EN-NE GitHub: BISHALTWR/Nepali-English-Translation-Dataset
Nepali Translation Parallel Corpus - EN-NE Google Drive
English-Nepali Translated Strings (TDIL) - UI/software localization TDIL-DC
English-Nepali Translation Instruction Dataset - EN-NE HF: ashokpoudel/English-Nepali-Translation-Instruction-Dataset

Multilingual and Specialized

Dataset Size Languages Domain Link
Trilingual Hindi-English-Nepali 200,000+ aligned triples HI-EN-NE - Kaggle: sundeepdawadi/cleaned-word2word-en-hi-ne
English-Nepali Translation (HF) - EN-NE Instruction-tuned HF: ashokpoudel/nepali-english-translation-dataset
Bidirectional English-Nepali MT for Legal Domain 125,000 legal sentences EN-NE Legal ACL Paper
CLE Parallel Corpus - EN-NE-UR - AI4Bharat: indicnlp_catalog

Historical and Shared Tasks

Dataset Event Link
WMT19 Parallel Corpus Shared task statmt.org/wmt19
FLORES 101 Dataset Multilingual benchmark GitHub: facebookresearch/flores

Instruction Tuning

Dataset Languages Type Link
Bactrian-X 50+ languages (includes Nepali) Instruction tuning HF: MBZUAI/Bactrian-X
Aya Dataset 101 languages (includes Nepali) Instruction tuning HF: cohere/aya_dataset

Speech and Audio Datasets

Audio data for automatic speech recognition and text-to-speech synthesis.

Large-Scale ASR

Dataset Size Description Link
OpenSLR-54 (Large Nepali ASR) 157,000 utterances, 400+ hours Google-supported, professional quality openslr.org/54
Mozilla Common Voice (Nepali) Crowdsourced speech, 100k+ clips available Diverse speakers commonvoice.mozilla.org/en/datasets
Nepali Speech to Text Dataset (Parliamentary) 1,000+ utterances From Parliament sessions (formal speech) Kaggle: ishworsubedii/nepali-speech-to-text-dataset
Nepali Automatic Speech Recognition (HF) Combined ASR dataset For transcription HF: amitpant7/Nepali-Automatic-Speech-Recognition
ASR Nepali 1 Large 50,000+ audio files With transcriptions Kaggle: sonismaharjan/asr-nepali-1-large
Amit Pant Nepali Speech-to-Text 2,650 rows, 949 MB Combined from OpenSLR SLR43 and Mozilla Common Voice, cleaned for ASR HF: amitpant7/nepali-speech-to-text
Rishi70612 Nepali ASR 5+ hours, 35 speakers YouTube-sourced Nepali speech, 30-second chunks HF: rishi70612/nepali_asr
DarviLab Nepali ASR Community Data - Community-contributed ASR data HF: darvilab/nepali-asr-community-data
Spktsagar OpenSLR Nepali ASR (Cleaned) - Cleaned version of OpenSLR Nepali ASR HF: spktsagar/openslr-nepali-asr-cleaned
IamTangsang OpenSLR54 Nepali ASR - OpenSLR54 Nepali ASR dataset HF: iamTangsang/OpenSLR54-Nepali-ASR
Zaxis018 Nepali Speech to Text - Speech recognition GitHub: Zaxis018/Nepali_speech_to_text

TTS and Synthesized Speech

Dataset Size Description Link
OpenSLR-43 (High quality TTS) High-quality single-speaker TTS data Professional recording openslr.org/43
Nepali Singing Voice Data Audio + lyrics For singing voice synthesis (music domain) Kaggle: pujancozu/nepali-singing-voice-data

Speech Analysis and Emotion

Dataset Size Description Link
Nepali Speech Emotion Detection 3,000+ speech samples With 6 emotion labels Kaggle: ashalupreti/nepali-speech-emotion-detection-dataset
Newari Music Classification Audio classification For Newari (related language) music Kaggle: pujancozu/newari-music

Multilingual Benchmarks

Dataset Description Link
Google FLEURS Multilingual benchmark including Nepali (101 languages) HF: google/fleurs

Computer Vision Datasets

Datasets for image/video captioning, object detection, and multimodal learning.

Sign Language and Gesture

Dataset Size Description Link
Nepali Sign Language Character Dataset 36 characters x 1,000 images = 36,000 total Sign language recognition Kaggle: biratpoudelrocks/nepali-sign-language-character-dataset
Nepali Sign Language Video Dataset (Zenodo) 630 professional videos 1,205 gestures with frame annotations, research-grade Zenodo: 10478554
Birat-Poudel Nepali Sign Language Character Dataset 36 characters x 1,000 images = 36,000 total Plain and random background versions, organized by character folders HF: Birat-Poudel/Nepali-Sign-Language-Character-Dataset

Image Captioning and Multimodal

Dataset Size Description Link
Flickr8k Nepali Captioning 8,000 images x 5 Nepali captions = 40,000 captions Adapted from Flickr8k English GitHub: bipeshrajsubedi/Flickr8k_Nepali_Dataset
Nepali Video Captioning (MSVD) 1,500+ videos With Nepali descriptions Kaggle: kabitaparajuli/video-captioning-in-nepali-msvd-dataset
MSVD Nepali Dataset 1,500+ videos Video captioning Kaggle: bipeshrajsubedi/msvd-nepali-dataset

Face Recognition and Emotion

Dataset Size Description Link
Nepali Celeb Localized Face Dataset 500+ Nepali celebrities With face bounding boxes GitHub: amitpant7/Nepali-Celeb-Localized-Face-Dataset
Facial Emotion Detection for Nepali Ethnic Groups 6,000+ facial images With 7 emotion labels Kaggle: suchanasubedi/facial-emotion-detection-for-nepali-ethnic-groups

Domain-Specific Objects

Dataset Size Description Link
Nepali Currency Dataset 5,000+ currency note images Banknote denomination classification Kaggle: uashutoshk/nepali-currency-dataset
Nepali Food Images 3,000+ images Of traditional Nepali dishes Kaggle: saurabkunwar/nepali-food-images
Nepali Cultural Dress and Ornaments 2,000+ images Of traditional clothing and artifacts Kaggle: bimarshakhanal/nepali-cultural-dress-and-ornaments
Nepali Vehicle Dataset 4,797 images Two-wheeler and four-wheeler vehicles from Nepal Kaggle: sdevkota007/vehicles-nepal-dataset
Nepali Vehicle Dataset (Aryal) - Nepali vehicle images Kaggle: aryalrupesh/nepli-vehicle-dataset
Vehicles Dataset Nepal - General vehicle dataset Kaggle: ishworsubedii/vehicles-dataset-nepal

Geospatial and Remote Sensing

Dataset Size Task Description Link
Nepal Landslide Dataset 230 GeoTIFF images + PNG masks Semantic segmentation Landslide scar detection for U-Net, scars in white, background in black Zenodo: 3675410 / Zenodo: 3688363

OCR and Handwriting Datasets

Character recognition, document digitization, and license plate detection.

Handwriting and Character Recognition

Dataset Size Description Link
Nepali Handwriting Characters Handwritten character images For OCR training Kaggle: mohanbhandari/nepali-handwriting-characters
Handwritten Devanagari Character Dataset 10,500+ images Of Devanagari script (applicable to Nepali) Kaggle: sa9arr/handwritten-devanagari-character-dataset
Nepali Handwritten Images for Text Detection Document-level Handwritten images for text detection Kaggle: sweekardahal/nepali-handwritten-images-for-text-detection
Dahalsweekar Nepali Handwritten Dataset Major Collection Comprehensive Camera-captured images of Nepali handwritten text from various regions GitHub: dahalsweekar/Nepali-Handwritten-Dataset-Major-Collection
Kaushu42 Nepali OCR - Handwriting recognition for Nepali characters GitHub: kaushu42/nepali-ocr
Prasanna1991 DHCD Dataset - Dataset of Devanagari (Nepali) handwritten characters GitHub: Prasanna1991/DHCD_Dataset
Deejungx NHCR - Nepali Handwritten Character Recognition using DHCD dataset GitHub: deejungx/nhcr
Rugz007 Devnagri OCR - Optical Character Recognition for Devanagari using TensorFlow 2 (96.63% accuracy) GitHub: Rugz007/Devnagri-OCR
Yashuv Handwritten Devanagari OCR - CNN + OpenCV for 46 classes (36 consonants + 10 numerals), 98% accuracy GitHub: yashuv/Handwritten-Devnagari-Optical-Character-Recognition
Nepali Handwritten Character Recognition (Zenodo) Research dataset Detailed annotations for handwritten characters Zenodo: 7472398
Improving Tesseract-OCR for Nepali (Zenodo) 5,000+ images Preprocessing techniques for OCR improvement Zenodo: 4361896
Gauravgiri Nepali OCR Dataset - Nepali OCR dataset HF: gauravgiri/nepali-ocr-dataset
Nahcol Nepali OCR Dataset - Nepali OCR dataset Kaggle: nahcol/nepali-ocr-dataset

License Plate and Vehicle Recognition

Dataset Size Description Link
Nepali License Plate (ALPR) V2 2,000+ license plate images For automatic license plate recognition Kaggle: ishworsubedii/alpr-v2
Nepali Motorbike Backplate Labeled 1,500+ motorcycle plate images With bounding boxes Kaggle: saugat111/nepali-moterbike-backplate-lbled

Lexicons and Linguistic Resources

Linguistic resources, dictionaries, and instruction-tuned datasets.

Dictionaries and Word Lists

Resource Size Type Link
Sabdabikash Synonym Word List 50,000+ Nepali words Thesaurus Kaggle: thenepaliguy/sabdabikash-synonym-nepali-word-list
Nepali Dictionary 25,000+ entries Definitions and examples Kaggle: sangamthapa/nepali-dictionary
Nepali Stopwords 400+ words Filtering Kaggle: sangamthapa/nepali-stopwords
Nepali Brihat Sabdakosh JSON 122,000 words Comprehensive dictionary (JSON format) GitHub: bikashpadhikari/nepali-brihat-sabdakosh-json
Nepali Names - Person names GitHub: datafiction/oya-nepali-nlp/blob/master/data/names/Nepali.txt
Dummy Nepali People Information - Synthetic person data GitHub: bibhuticoder/dummydata/blob/master/data.csv
Nepali Unigrams Cleaned 200k+ unique words Vocabulary with frequency Kaggle: thenepaliguy/nepali-unigrams-cleaned
Nepali Transliteral Dataset - Transliteration (Unicode Nepali to Latin script mapping) GitHub: SushilShrestha/NepaliTransliteralDataset

Morphology and Syntax

Resource Size Type Link
Nepali POS Data (UPOS Mapped) 3,000+ tagged sentences POS tags following Universal Dependencies standard Kaggle: thenepaliguy/nepali-pos
Nepali Word-Lemma Gold Data 5,000+ words Manual lemmatization annotations GitHub: dpakpdl/NepaliLemmatizer/tree/master/Lemmatization/data/manually_annotated_corpus
Universal Dependencies (UD) Nepali 17,500+ tokens Full syntactic dependency annotations (official UD project) GitHub: UniversalDependencies/UD_Nepali-NPP

Instruction Tuning and Multilingual

Resource Languages Type Link
Bactrian-X (Instruction Tuning) Nepali included in multilingual instruction-tuning dataset (50+ languages) HF: MBZUAI/Bactrian-X
Aya Dataset (Instruction Tuning) Nepali included in community-driven instruction dataset (101 languages) HF: cohere/aya_dataset

Pre-trained Models and Embeddings

Pre-computed word vectors and language models with training datasets.

Large Language Models

Model Parameters Training Data Link
IRIISNEPAL RoBERTa 110M params 27.5 GB from 99 news sites HF: IRIISNEPAL/RoBERTa_Nepali_110M
NepaliBERT - 4.6 GB, 85k+ articles HF: Shushant/nepaliBERT
DistilGPT2-Nepali - 13M Nepali sequences (OSCAR + CC100 + Wikipedia) HF: Sakonii/distilgpt2-nepali
Nepali Text Generation (Transformer) - Custom GitHub: NirajanBekoju/Transformer-Based-Nepali-Language-Model
NepBERTa - GLUE benchmark baseline nepberta.github.io
NepaliGPT - - arXiv: 2506.16399
Sidskarki Qwen3 ASR Nepali - Qwen3 model fine-tuned for Nepali ASR HF: sidskarki/Qwen3-ASR-Nepali

Word Embeddings

Embedding Dimensions Vocabulary Link
Nepali Word2Vec from scratch Custom-trained 300D vectors With training scripts GitHub: R4j4n/Nepali-Word2Vec-from-scratch
300D Word2Vec Embeddings for Nepali Language Pre-computed 300D vectors 20k+ words GitHub: rabindralamsal/Word2Vec-Embeddings-for-Nepali-Language
Nepali FastText Word Vectors Official FastText vectors Common Crawl + Wikipedia fastText: crawl-vectors

Fine-tuned Models

Model Task Dataset Link
Fine-tuned DistilBERT on 16 Newsgroup News classification - HF: Suyogyart/nepali-16-newsgroups-classification

Tools and Frameworks

Complete NLP toolkits and utilities for Nepali processing.

Tool Description Link
Nepali Lemmatizer Rule-based lemmatization with training data GitHub: dpakpdl/NepaliLemmatizer/tree/master/Lemmatization/data
Nepali Transliteration Script conversion dataset for transliteration tasks Kaggle: saugatkafley/nepali-transliteration
Audinp (Data Collector) Tool for collecting speech data (contributed to OpenSLR-54) GitHub: SUBOdhar/audinp
BISH-100 (AI Anchor) Synthetic video dataset with AI-generated Nepali anchor Kaggle: bisheshworneupane/bish-100-nepali-text-driven-ai-anchor
Fine-tuned DistilBERT on 16 Newsgroup Dataset Ready-to-use classifier for news categorization -
Pemagrg1 Nepali-Datasets Comprehensive list of Nepali dataset sources GitHub: pemagrg1/Nepali-Datasets
IOST-ASCOL Nepali Datasets Curated collection of ML, NLP, audio, images, and geospatial data GitHub: IOST-ASCOL/nepali-datasets
CodeforNepal Data Open data repository for Nepal GitHub: CodeforNepal/data
Sandip BG Nepal Data Nepal-related datasets GitHub: sandipbgt/nepal-data
Open Knowledge Nepal Open knowledge resources GitHub: openknowledgenp
R4j4n Nepali-Dataset Additional Nepali datasets GitHub: R4j4n/Nepali-Dataset
Madan Baduwal CV Datasets Computer vision datasets for Nepal GitHub: madanbaduwal/cv-datasets
HBVJ99 Nepal-Datasets Various Nepal datasets GitHub: hbvj99/Nepal-Datasets
Kaushu42 Nepali OCR Handwriting recognition for Nepali characters GitHub: kaushu42/nepali-ocr
Prasanna1991 DHCD Dataset Dataset of Devanagari (Nepali) handwritten characters GitHub: Prasanna1991/DHCD_Dataset
Deejungx NHCR Nepali Handwritten Character Recognition using DHCD dataset GitHub: deejungx/nhcr
Rugz007 Devnagri OCR Optical Character Recognition for Devanagari using TensorFlow 2 (96.63% accuracy) GitHub: Rugz007/Devnagri-OCR
Yashuv Handwritten Devanagari OCR CNN + OpenCV for 46 classes (36 consonants + 10 numerals), 98% accuracy GitHub: yashuv/Handwritten-Devnagari-Optical-Character-Recognition

Research Papers

Peer-reviewed publications on Nepali NLP and related work.

Recent and High-Impact (2024-2026)

Paper Year Focus Link
NepaliGPT: A Generative Language Model for the Nepali Language 2025 Recent LLM research arXiv: 2506.16399
NLUE (Nepali Language Understanding Evaluation) 2024 9 NLU tasks with comprehensive benchmark arXiv: 2411.19244
IRIISNEPAL RoBERTa: State-of-the-art Nepali LM 2024 27.5 GB training corpus from 99 news sites arXiv: 2411.15734
Code-Mixed Nepali-English Abuse Detection 2025 5k annotated code-mixed dataset arXiv: 2504.21026
Nepali Transformers at NLU of Devanagari Script Languages 2025 2025 Transformer architectures for Devanagari ACL: 2025.chipsal-1.36
Application of Nepali Large Language Models to Improve Sentiment 2024 LLM applications ACM
NepKanun: A RAG-Based Nepali Legal Assistant 2025 RAG systems for legal domain OpenReview
Exploring NLP Challenges for Nepali 2024 Overview of remaining challenges Preprints: 202409.1229

Sentiment Analysis and Classification

Paper Focus Link
Aspect Based Sentiment Analysis of Nepali Text Using SVM and Naive Bayes Comparative ML approach ResearchGate
An Analysis of Classification Algorithms for Nepali News Benchmark of various classifiers ResearchGate
Nepali Text Document Classification Using Deep Neural Network Deep learning approaches NEPJOL

NLP Tasks and Applications

Paper Task Link
A Machine Learning Approach to Anaphora Resolution in Nepali Language Pronoun resolution task IEEE
Nepali Image Captioning Vision-language multimodal task IEEE: 8947436
Named-Entity Based Sentiment Analysis of Nepali News Media Texts NER + sentiment joint modeling ACL Anthology
Topic Modeling for Nepali Political News Topic analysis in news domain IEEE: 11004776

Linguistic and Historical

Paper Focus Link
Natural language processing for Nepali text: a review Comprehensive NLP review Springer
A Descriptive Grammar of Nepali and an Analyzed Corpus Linguistic grammar reference Google Books
Nepali Spell Checker 1.1 and the Thesaurus Early spell checking research Wayback: NEP05.pdf
Nepali Spell Checker Earlier spell checking work Wayback: NEP04.pdf

Research Aggregators

Resource Description Link
Nepali NLP Progress (RayGone) Comprehensive tracker (maintained) GitHub: RayGone/Nepali-NLP-Progress
Nepali NLP Progress (divyamani1) Community-maintained research tracker GitHub: divyamani1/Nepali-NLP-Progress
Curated List of Nepali NLP Resources (Ghimire Sunil) Comprehensive resource list GitHub: ghimiresunil/Curated-List-of-Nepali-NLP-Resources
Nepali NLP Resources (rameshhpathak) Tools and dataset aggregator with descriptions GitHub: rameshhpathak/nepali-nlp-resources
Nepali Datasets (pemagrg1) Collection of Nepali datasets GitHub: pemagrg1/Nepali-Datasets
Nepali Datasets (IOST-ASCOL) Nepali datasets repository GitHub: IOST-ASCOL/nepali-datasets
Nepali Dataset (R4j4n) Nepali dataset collection GitHub: R4j4n/Nepali-Dataset
ML Datasets (amitness) General ML datasets, includes Nepali resources GitHub: amitness/ml-datasets

Open Data and Government Resources

Official government datasets and open data portals.

Resource Description Link
Open Data Nepal Official open data portal with 500+ government datasets (health, education, infrastructure) opendatanepal.com
Census Nepal Official census data from Central Bureau of Statistics (demographic, geographic, economic) censusnepal.cbs.gov.np/results
Nepal Multi-District Weather Dataset (2020-2025) Meteorological data across districts Kaggle: dipeshthapa1/nepal-multi-district-weather-dataset-2020-2025
Nepal Earthquake Seismicity Dataset (1990-2026) Historical earthquake data Kaggle: amansinghnp/nepal-earthquake-seismicity-dataset-1990-2026
House Price Dataset Nepal Real estate pricing Kaggle: nishanpokh/house-price-dataset-nepal
Nepal Trekking Dataset Tourism routes Kaggle: bibekrai44/nepal-treking-dataset
Nepali Election Results Historical Political data Kaggle: dimanjung/nepali-election-results-historical
Gender Based Violence in Nepal 2019-2026 Social data Kaggle: aneeshmhj/gender-based-violence-in-nepal-2019-2026

Additional Resources

Specialized Collections and Aggregators

Resource Description Link
Comprehensive Nepali Datasets (IOST-ASCOL) Aggregated NLP, speech, image, geospatial datasets GitHub: IOST-ASCOL/nepali-datasets
ML Datasets for Nepal Curated ML resources including Laxmi Prasad Devkota Poems (119k characters) and Brihat Sabdakosh GitHub: amitness/ml-datasets
IndicNLP Catalog (AI4Bharat) Official Indic language resources (11 languages including Nepali) ai4bharat.github.io/indicnlp_catalog

Code-Mixed and Multilingual NLP Datasets

Dataset Description Link
Code-Mixed Nepali-English Abuse Detection 5,000 Nepali-English code-mixed comments Social media
Nepali-English Code-Switched LID, POS, NER, Sentiment Complete NLP pipeline for code-mixed data GitHub: sagorbrur/codeswitch
CLE Parallel Corpus (AI4Bharat) English-Nepali-Urdu parallel data Multilingual

Legal and Government Text Corpora

Constitution and Acts

Dataset Size Description Link
Nepal Constitution Dataset - Complete Nepali Constitution text HF: ranjitraut/nepal-constitution-dataset
Nepal Section-wise Act Datasets - Collection of Nepali legal acts organized by sections HF: ranjitraut/nepal-section-wise-act-datasets

Computer Vision Datasets

Domain-Specific Objects

Dataset Size Description Link
Nepali Currency Dataset 5,000+ currency note images Banknote denomination classification Kaggle: uashutoshk/nepali-currency-dataset
Nepali Currency High-Resolution Image Datasets - High-resolution images of Nepali currency notes Kaggle: theranjitraut/nepali-currency-high-resolution-image-datasets
Nepali Food Images 3,000+ images Of traditional Nepali dishes Kaggle: saurabkunwar/nepali-food-images
Nepali Cultural Dress and Ornaments 2,000+ images Of traditional clothing and artifacts Kaggle: bimarshakhanal/nepali-cultural-dress-and-ornaments
Nepali Vehicle Dataset 4,797 images Two-wheeler and four-wheeler vehicles from Nepal Kaggle: sdevkota007/vehicles-nepal-dataset
Nepali Vehicle Dataset (Aryal) - Nepali vehicle images Kaggle: aryalrupesh/nepli-vehicle-dataset
Vehicles Dataset Nepal - General vehicle dataset Kaggle: ishworsubedii/vehicles-dataset-nepal

Sports

Dataset Size Description Link
Futvar Football Players Detection Dataset - Football (soccer) players detection for object detection tasks Roboflow: ranjit-raut-do9me/futvar-football-players-detection-dataset

Ethical Considerations

  • Sentiment/Hate Speech Data: Contains potentially offensive language; bias mitigation recommended for model training
  • Social Media Data (Tweets, Instagram): May contain personal information; use with GDPR/privacy compliance
  • Copyright: Wikipedia, news articles sourced responsibly; attribution recommended
  • Multilingual Data: Code-mixed datasets reflect real-world language use; social biases may be present

Quick Links

Dataset Summary

Category Count Description
Text Corpus 30+ Ultra-large, large curated, and specialized text collections
NLP Datasets 40+ Classification, NER, QA, Summarization, Sentiment, Hate Speech
Translation Data 15+ Parallel corpora for EN-NE, HI-NE, UR-NE, and multilingual
Speech and Audio 15+ ASR, TTS, emotion detection datasets
Computer Vision 15+ Sign language, image captioning, face recognition, object detection
OCR and Handwriting 15+ Character recognition, license plate detection
Lexicons 10+ Dictionaries, stopwords, POS data, word embeddings
Pre-trained Models 10+ RoBERTa, BERT, GPT2, word embeddings
Benchmarks 10+ NLUE, Nep-gLUE, FLORES-101, IndicBench
Research Papers 25+ Recent publications and historical works
Tools and Frameworks 15+ NLP toolkits, utilities, dataset aggregators
Open Data 10+ Government and public datasets

Dataset Search Guide

General Web Search Strategies

Google Search Operators for Nepali Datasets

Search Type Query Template Example
Basic dataset search Nepali dataset OR "nepali" dataset OR nepali corpus site:PLATFORM Nepali NLP dataset site:github.com
Recent datasets (2024-2026) Nepali dataset (2024 OR 2025 OR 2026) site:PLATFORM Nepali dataset 2025 site:huggingface.co
Specific task Nepali [TASK] dataset OR corpus Nepali OCR dataset
File type filter Nepali dataset filetype:json OR filetype:csv OR filetype:zip Nepali NER dataset filetype:json
Language code filter language:ne OR language:nep OR nepali language dataset language:ne dataset site:huggingface.co
Devanagari script Devanagari dataset OR "Devanagari script" dataset Devanagari OCR dataset
Code-mixed data Nepali-English code-mixed dataset OR code-switched Nepali-English code-mixed sentiment dataset
Academic sources Nepali dataset site:arxiv.org OR site:zenodo.org OR site:researchgate.net Nepali NLP dataset site:zenodo.org

Google Advanced Search Tips

  • Use "Nepali" OR "nepali" OR "ne" to catch all variations
  • Add site: operator to limit to specific platforms
  • Use intitle: to find datasets in titles: intitle:"Nepali dataset"
  • Use inurl: to find in URLs: inurl:nepali inurl:dataset
  • Filter by date: Click "Tools" -> "Any time" -> "Past year" or custom range
  • Use filetype: to find specific formats: filetype:csv Nepali

Hugging Face Datasets Search

Direct Search Methods

Web Interface Search

  • Main page: https://huggingface.co/datasets
  • Language filter: Click "Language" -> Select "Nepali (ne)" or search language:ne
  • Search bar: Type nepali or ne or language:ne

Advanced Search Queries

Query Result Link
language:ne All Nepali language datasets HF: datasets?language=ne
nepali Datasets with "nepali" in name/description HF: datasets?q=nepali
other=nepali Datasets tagged with Nepali HF: datasets?other=nepali
nepali AND asr Nepali ASR datasets HF: datasets?q=nepali+asr
nepali AND (ocr OR vision OR image) Nepali CV datasets HF: datasets?q=nepali+(ocr+OR+vision+OR+image)
nepali AND (ner OR sentiment OR classification) Nepali NLP datasets HF: datasets?q=nepali+(ner+OR+sentiment+OR+classification)
nepali AND translation Translation datasets HF: datasets?q=nepali+translation
nepali AND (2024 OR 2025 OR 2026) Recent datasets HF: datasets?q=nepali+(2024+OR+2025+OR+2026)

Sorting and Filtering

  • Sort by: "Most recent", "Most downloads", "Most likes"
  • Filter by: Task (text-classification, automatic-speech-recognition, etc.)
  • Filter by: License (MIT, Apache, Creative Commons)
  • Filter by: Size (Small <1GB, Medium 1-10GB, Large >10GB)

Hugging Face API Search

from datasets import load_dataset_builder
from huggingface_hub import HfApi

# Method 1: Using HfApi
api = HfApi()
datasets = api.list_datasets(filter="nepali")
for ds in datasets:
    print(f"{ds.id} - {ds.description}")

# Method 2: Using load_dataset_builder
try:
    dataset = load_dataset_builder("nepali-dataset-name")
    print(dataset.info)
except:
    print("Dataset not found")

# Method 3: Search with language filter
from huggingface_hub import list_datasets
datasets = list_datasets(filter="language:ne")

Hugging Face CLI

# Install: pip install huggingface_hub
huggingface-cli scan-cache
huggingface-cli list datasets --filter nepali
huggingface-cli download dataset-name

Browser Bookmarklets

Create bookmarklets for quick access:

All Nepali Datasets:

javascript:window.location.href='https://huggingface.co/datasets?language=ne'

Nepali ASR Datasets:

javascript:window.location.href='https://huggingface.co/datasets?q=nepali+automatic-speech-recognition&sort=modified'

Nepali NLP Datasets:

javascript:window.location.href='https://huggingface.co/datasets?q=nepali+(ner+OR+sentiment+OR+classification)&sort=downloads'

GitHub Search Strategies

Direct Search Methods

GitHub Web Search

Search Queries

Query Result Link
nepali dataset All Nepali dataset repos GitHub: nepali dataset
nepali nlp NLP-related repos GitHub: nepali nlp
nepali corpus Text corpus repos GitHub: nepali corpus
nepali ocr OCR datasets GitHub: nepali ocr
nepali speech Speech/audio datasets GitHub: nepali speech
nepali computer vision CV datasets GitHub: nepali computer vision
nepali handwritten Handwriting datasets GitHub: nepali handwritten
nepali sign language Sign language datasets GitHub: nepali sign language
language:nepali Repos with Nepali as primary language GitHub: language:nepali
topic:nepali-nlp NLP topic repos GitHub: topic:nepali-nlp
topic:nepali-dataset Dataset topic repos GitHub: topic:nepali-dataset
topic:nepali-character-recognition OCR/character recognition GitHub: topic:nepali-character-recognition

GitHub Advanced Filters

  • Sort by: "Recently updated", "Most stars", "Most forks"
  • Filter by: Language (Python, Jupyter Notebook, etc.)
  • Filter by: License (MIT, Apache, etc.)
  • Filter by: Date range (Created/Updated)
  • Filter by: Repository type (Public, Sources, Forks)

GitHub API Search

import requests
import json

# Search repositories
url = "https://api.github.com/search/repositories"
params = {
    "q": "nepali dataset language:python",
    "sort": "updated",
    "order": "desc",
    "per_page": 100
}
headers = {"Accept": "application/vnd.github.v3+json"}

response = requests.get(url, params=params, headers=headers)
repos = response.json()["items"]
for repo in repos:
    print(f"{repo['name']} - {repo['html_url']} - Stars: {repo['stargazers_count']}")

# Search code
url = "https://api.github.com/search/code"
params = {
    "q": "nepali dataset extension:json OR extension:csv",
    "per_page": 100
}
response = requests.get(url, params=params, headers=headers)

GitHub CLI (gh)

# Install: https://cli.github.com/
gh auth login

# Search repos
gh search repos "nepali dataset" --sort updated --order desc
gh search repos "nepali nlp" --language python
gh search repos "topic:nepali-dataset"

# Clone found repos
gh repo clone OWNER/REPO

GitHub Topics to Follow

Kaggle Search Strategies

Direct Search Methods

Kaggle Web Search

Search Queries

Query Result Link
nepali All Nepali datasets Kaggle: nepali
nepali nlp NLP datasets Kaggle: nepali nlp
nepali ocr OCR datasets Kaggle: nepali ocr
nepali speech Speech datasets Kaggle: nepali speech
nepali computer vision CV datasets Kaggle: nepali computer vision
nepali handwritten Handwriting datasets Kaggle: nepali handwritten
nepali sign language Sign language datasets Kaggle: nepali sign language
nepali text Text datasets Kaggle: nepali text
nepali classification Classification datasets Kaggle: nepali classification
nepali sentiment Sentiment datasets Kaggle: nepali sentiment

Kaggle Tags

Kaggle Advanced Filters

  • Sort by: "Most Votes", "Most Recent", "Most Views", "Most Downloads"
  • Filter by: License (CC0, CC-BY, Apache, etc.)
  • Filter by: Size (Small, Medium, Large)
  • Filter by: Usability (Public, Private)

Kaggle API Search

from kaggle.api.kaggle_api_extended import KaggleApi

api = KaggleApi()
api.authenticate()

# Search datasets
datasets = api.dataset_list(search="nepali")
for ds in datasets:
    print(f"{ds.ref} - {ds.title}")

# Download dataset
api.dataset_download_files('username/dataset-name', path='./data', unzip=True)

# Search with filters
datasets = api.dataset_list(
    search="nepali",
    tag_ids=["16979"],  # Nepali language tag
    sort_by="votes",
    max_size="1GB"
)

Kaggle CLI

# Install: pip install kaggle
kaggle datasets list -s nepali
kaggle datasets list -s "nepali nlp"
kaggle datasets list -s nepali --sort-by votes
kaggle datasets download username/dataset-name

Roboflow Search Strategies

Direct Search Methods

Roboflow Universe Search

Search Queries

Query Result Link
nepali All Nepali datasets Roboflow: nepali
nepali object detection Object detection datasets Roboflow: nepali object detection
nepali classification Classification datasets Roboflow: nepali classification
nepali sign language Sign language datasets Roboflow: nepali sign language
nepali vehicle Vehicle detection datasets Roboflow: nepali vehicle
nepali currency Currency detection Roboflow: nepali currency
nepali food Food recognition Roboflow: nepali food
nepali cultural Cultural heritage Roboflow: nepali cultural
devanagari Devanagari script datasets Roboflow: devanagari
nepali character Character recognition Roboflow: nepali character

Roboflow Filters

  • Task type: Object Detection, Classification, Segmentation, etc.
  • License: Public, Private, Commercial
  • Image count: Filter by number of images
  • Last updated: Filter by recency
  • Annotations: Bounding boxes, polygons, etc.

Roboflow API Search

import requests

# Search datasets
url = "https://universe.roboflow.com/api/search"
params = {
    "query": "nepali",
    "page": 1,
    "per_page": 20
}
headers = {"Accept": "application/json"}

response = requests.get(url, params=params, headers=headers)
datasets = response.json()["results"]
for ds in datasets:
    print(f"{ds['name']} - {ds['url']} - Images: {ds['image_count']}")

# Get dataset details
dataset_id = "dataset-id"
url = f"https://universe.roboflow.com/api/dataset/{dataset_id}"
response = requests.get(url, headers=headers)
dataset = response.json()

Roboflow CLI

# Install: pip install roboflow
from roboflow import Roboflow
rf = Roboflow(api_key="YOUR_API_KEY")

# Search datasets
datasets = rf.search("nepali")
for ds in datasets:
    print(ds)

# Download dataset
project = rf.workspace("workspace-name").project("project-name")
dataset = project.version(1).download("yolov8")

Zenodo Search Strategies

Direct Search Methods

Zenodo Web Search

Search Queries

Query Result Link
nepali dataset All Nepali datasets Zenodo: nepali dataset
nepali nlp NLP datasets Zenodo: nepali nlp
nepali ocr OCR datasets Zenodo: nepali ocr
nepali handwritten Handwriting datasets Zenodo: nepali handwritten
nepali speech Speech datasets Zenodo: nepali speech
nepali computer vision CV datasets Zenodo: nepali computer vision
nepal landslide Landslide datasets Zenodo: nepal landslide
nepali sign language Sign language datasets Zenodo: nepali sign language
devanagari Devanagari script Zenodo: devanagari
subject:"computer vision" nepali CV datasets Zenodo: CV Nepali

Zenodo Advanced Filters

  • Type: Dataset, Software, Publication, etc.
  • Subject: Computer Science, Linguistics, etc.
  • Date range: Filter by publication date
  • Access: Open Access, Restricted, etc.
  • License: Creative Commons, MIT, etc.

Zenodo API Search

import requests

# Search datasets
url = "https://zenodo.org/api/records/"
params = {
    "q": "nepali dataset",
    "type": "dataset",
    "size": 20,
    "page": 1
}
headers = {"Accept": "application/json"}

response = requests.get(url, params=params, headers=headers)
datasets = response.json()["hits"]["hits"]
for ds in datasets:
    print(f"{ds['metadata']['title']} - {ds['links']['html']}")

# Get specific dataset
record_id = "1234567"
url = f"https://zenodo.org/api/records/{record_id}"
response = requests.get(url, headers=headers)
dataset = response.json()

Popular Nepali Datasets on Zenodo

Other Dataset Platforms

Open Data Portals

Open Data Nepal

Search queries:

Government of Nepal Data Portal

World Bank Open Data (Nepal)

import requests
import pandas as pd

# World Bank API for Nepal data
url = "https://api.worldbank.org/v2/country/NPL/indicator"
params = {
    "format": "json",
    "per_page": 100
}
response = requests.get(url, params=params)
data = response.json()

Academic Repositories

IEEE Dataport

Figshare

Dryad

Harvard Dataverse

Mendeley Data

Specialized AI/ML Platforms

Papers With Code (Datasets)

Google Dataset Search

Advanced queries:

  • nepali dataset site:huggingface.co
  • nepali corpus site:kaggle.com
  • nepali nlp site:github.com

Data.gov (US) - International Data

AWS Open Data Registry

Microsoft Research Open Data

Social Media and Community Platforms

Reddit

Search operators:

  • nepali dataset OR corpus OR collection
  • site:reddit.com nepali nlp

Twitter/X

LinkedIn

Discord and Slack Communities

  • Join Nepali NLP, AI4Bharat, Hugging Face Discord servers
  • Search for #nepali-datasets or #nepali-nlp channels

Niche Platforms

OpenSLR (Speech and Audio)

LDC (Linguistic Data Consortium)

ELRA (European Language Resources Association)

Common Voice (Mozilla)

Flickr (Image Datasets)

Wikimedia Commons

Advanced Search Techniques

Boolean Search Operators

Operator Example Result
AND nepali AND dataset Both terms must appear
OR nepali OR nepali OR ne Any term can appear
NOT nepali NOT english Excludes "english"
Quotes "nepali dataset" Exact phrase
Parentheses (nepali OR nepali) AND (dataset OR corpus) Grouped logic
Wildcard nepali* Matches nepali, nepalis, etc.
Site site:huggingface.co nepali dataset Only on Hugging Face
Filetype nepali dataset filetype:json Only JSON files
Intitle intitle:"nepali dataset" In page title
Inurl inurl:nepali inurl:dataset In URL

Regular Expression Search

Use regex for more precise matching:

Pattern Example Matches
nepali[\s-]?dataset nepali dataset, nepali-dataset Both variations
(nepali|nepali) nepali or nepali Either spelling
\bnepali\b Whole word "nepali" Not "nepalis" or "nepalese"
nepali.*corpus nepali corpus, nepali text corpus Any text between
dataset.*nepali.*202[4-6] Recent Nepali datasets Datasets from 2024-2026

Semantic Search with LLMs

Use Large Language Models to find datasets:

from langchain_community.vectorstores import Chroma
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain.text_splitter import CharacterTextSplitter
from langchain_community.document_loaders import WebBaseLoader
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnablePassthrough
from langchain_core.output_parsers import StrOutputParser

# Method 1: Semantic search on dataset descriptions
model_name = "sentence-transformers/all-mpnet-base-v2"
embeddings = HuggingFaceEmbeddings(model_name=model_name)

# Load dataset metadata
loader = WebBaseLoader(["https://huggingface.co/datasets?language=ne"])
docs = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
texts = text_splitter.split_documents(docs)

# Create vector store
db = Chroma.from_documents(texts, embeddings)
retriever = db.as_retriever(search_kwargs={"k": 5})

# Query
query = "Find Nepali OCR datasets with handwritten characters"
docs = retriever.invoke(query)
for doc in docs:
    print(doc.page_content)

# Method 2: LLM-powered search
template = """You are an expert at finding Nepali datasets.
Given the user's query, suggest relevant search terms and platforms.

Query: {query}
Suggestions:"""

prompt = ChatPromptTemplate.from_template(template)
chain = (
    {"query": RunnablePassthrough()}
    | prompt
    | model
    | StrOutputParser()
)

result = chain.invoke("I need Nepali speech recognition datasets")
print(result)

Mobile and Browser Tools

Browser Extensions

Dataset Search Extensions

  • Google Dataset Search Extension: Quick access to Google Dataset Search
  • Hugging Face Quick Search: Add HF search to your browser
  • GitHub Octotree: Better GitHub repo navigation

Custom Search Engines (Chrome) Create custom search engines in Chrome:

Hugging Face Nepali Datasets:

GitHub Nepali:

Kaggle Nepali:

Usage: Type hfnep ocr in Chrome address bar -> searches Hugging Face for "ocr language:ne"

Mobile Apps

GitHub Mobile App

  • Search for nepali dataset or nepali nlp
  • Save searches for quick access

Kaggle Mobile

  • Browse datasets by language: Nepali
  • Follow Nepali dataset tags

Hugging Face Mobile

  • Access datasets on mobile browser
  • Bookmark Nepali language filter

Custom Shortcuts (iOS/Android) Create shortcuts for frequent searches:

iOS Shortcut for Nepali Datasets:

  1. Open Shortcuts app
  2. Create new shortcut
  3. Add "Open URLs" action
  4. URL: https://huggingface.co/datasets?language=ne
  5. Name: "Nepali Datasets"

Android Widget: Use browser bookmark widgets with pre-saved searches

Automated Dataset Discovery

Python Script for Multi-Platform Search

import requests
import json
from datetime import datetime, timedelta
from typing import List, Dict, Optional

class NepaliDatasetSearcher:
    def __init__(self):
        self.platforms = {
            "huggingface": "https://huggingface.co/api/datasets",
            "github": "https://api.github.com/search/repositories",
            "kaggle": "https://www.kaggle.com/api/v1/datasets/list",
            "zenodo": "https://zenodo.org/api/records/",
            "roboflow": "https://universe.roboflow.com/api/search"
        }
        self.headers = {
            "User-Agent": "NepaliDatasetSearcher/1.0",
            "Accept": "application/json"
        }

    def search_huggingface(self, query: str = "nepali", language: str = "ne",
                          task: Optional[str] = None, limit: int = 20) -> List[Dict]:
        """Search Hugging Face datasets"""
        url = f"{self.platforms['huggingface']}?search={query}"
        if language:
            url += f"&language={language}"
        if task:
            url += f"&task={task}"
        url += f"&limit={limit}"

        response = requests.get(url, headers=self.headers)
        if response.status_code == 200:
            return response.json().get("datasets", [])
        return []

    def search_github(self, query: str = "nepali dataset", language: Optional[str] = None,
                     sort: str = "updated", order: str = "desc", limit: int = 20) -> List[Dict]:
        """Search GitHub repositories"""
        params = {
            "q": query,
            "sort": sort,
            "order": order,
            "per_page": limit
        }
        if language:
            params["q"] += f" language:{language}"

        response = requests.get(self.platforms['github'], params=params, headers=self.headers)
        if response.status_code == 200:
            return response.json().get("items", [])
        return []

    def search_kaggle(self, query: str = "nepali", limit: int = 20) -> List[Dict]:
        """Search Kaggle datasets (requires API key)"""
        from kaggle.api.kaggle_api_extended import KaggleApi
        api = KaggleApi()
        api.authenticate()

        datasets = []
        try:
            results = api.dataset_list(search=query, max_size=limit)
            for r in results:
                datasets.append({
                    "ref": r.ref,
                    "title": r.title,
                    "category": r.category,
                    "voteCount": r.voteCount,
                    "downloadCount": r.downloadCount,
                    "url": f"https://www.kaggle.com/datasets/{r.ref}"
                })
        except Exception as e:
            print(f"Kaggle API error: {e}")
        return datasets

    def search_zenodo(self, query: str = "nepali dataset", limit: int = 20) -> List[Dict]:
        """Search Zenodo records"""
        params = {
            "q": query,
            "type": "dataset",
            "size": limit,
            "page": 1
        }
        response = requests.get(self.platforms['zenodo'], params=params, headers=self.headers)
        if response.status_code == 200:
            hits = response.json().get("hits", {}).get("hits", [])
            return [{"title": h["metadata"]["title"],
                     "url": h["links"]["html"],
                     "date": h["metadata"].get("publication_date"),
                     "description": h["metadata"].get("description")}
                    for h in hits]
        return []

    def search_roboflow(self, query: str = "nepali", limit: int = 20) -> List[Dict]:
        """Search Roboflow Universe"""
        params = {"query": query, "page": 1, "per_page": limit}
        response = requests.get(self.platforms['roboflow'], params=params, headers=self.headers)
        if response.status_code == 200:
            return response.json().get("results", [])
        return []

    def search_all(self, query: str = "nepali", limit: int = 10) -> Dict[str, List[Dict]]:
        """Search all platforms"""
        results = {
            "huggingface": self.search_huggingface(query, limit=limit),
            "github": self.search_github(query, limit=limit),
            "zenodo": self.search_zenodo(query, limit=limit),
            "roboflow": self.search_roboflow(query, limit=limit)
        }

        try:
            results["kaggle"] = self.search_kaggle(query, limit=limit)
        except:
            results["kaggle"] = []

        return results

    def get_recent_datasets(self, days: int = 30, limit: int = 20) -> Dict[str, List[Dict]]:
        """Get datasets updated in last N days"""
        since_date = (datetime.now() - timedelta(days=days)).strftime("%Y-%m-%d")

        results = {
            "huggingface": self.search_huggingface(
                query=f"nepali updated:>{since_date}",
                limit=limit
            ),
            "github": self.search_github(
                query=f"nepali dataset created:>{since_date}",
                sort="updated",
                limit=limit
            ),
            "zenodo": self.search_zenodo(
                query=f"nepali dataset",
                limit=limit
            )
        }
        return results

# Usage
searcher = NepaliDatasetSearcher()

# Search all platforms
all_results = searcher.search_all("nepali ocr", limit=5)
for platform, datasets in all_results.items():
    print(f"\n=== {platform.upper()} ===")
    for ds in datasets[:3]:
        print(f"- {ds.get('title', ds.get('name', ds.get('ref', 'N/A')))}")
        print(f"  {ds.get('url', ds.get('html_url', 'N/A'))}")

# Get recent datasets
recent = searcher.get_recent_datasets(days=7, limit=5)
print("\n=== RECENT DATASETS (Last 7 days) ===")
for platform, datasets in recent.items():
    if datasets:
        print(f"\n{platform}: {len(datasets)} new datasets")

Scheduled Dataset Monitoring

Set up a cron job or scheduled task to check for new Nepali datasets:

import schedule
import time
from nepali_dataset_searcher import NepaliDatasetSearcher

def check_new_datasets():
    searcher = NepaliDatasetSearcher()
    recent = searcher.get_recent_datasets(days=1, limit=10)

    new_datasets = []
    for platform, datasets in recent.items():
        if datasets:
            new_datasets.append(f"Found {len(datasets)} new datasets on {platform}")

    if new_datasets:
        print("\n".join(new_datasets))
        send_notification("\n".join(new_datasets))

def send_notification(message: str):
    """Send notification via email, Slack, etc."""
    webhook_url = "YOUR_SLACK_WEBHOOK"
    payload = {"text": f"New Nepali Datasets Alert!\n{message}"}
    requests.post(webhook_url, json=payload)

# Schedule daily checks
schedule.every().day.at("09:00").do(check_new_datasets)
schedule.every().day.at("21:00").do(check_new_datasets)

while True:
    schedule.run_pending()
    time.sleep(3600)

GitHub Actions for Dataset Monitoring

Create a .github/workflows/monitor-datasets.yml file:

name: Monitor Nepali Datasets
on:
  schedule:
    - cron: '0 9,21 * * *'
  workflow_dispatch:

jobs:
  check-datasets:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: '3.10'

      - name: Install dependencies
        run: |
          python -m pip install --upgrade pip
          pip install requests kaggle huggingface_hub

      - name: Run dataset monitor
        env:
          KAGGLE_USERNAME: ${{ secrets.KAGGLE_USERNAME }}
          KAGGLE_KEY: ${{ secrets.KAGGLE_KEY }}
          SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
        run: |
          python scripts/monitor_datasets.py

      - name: Commit updates
        run: |
          git config --global user.name "Dataset Monitor"
          git config --global user.email "monitor@example.com"
          git add data/new_datasets.json
          git commit -m "Update: New Nepali datasets found [$(date +%Y-%m-%d)]"
          git push

Create scripts/monitor_datasets.py:

import json
import os
from datetime import datetime
from nepali_dataset_searcher import NepaliDatasetSearcher

def load_existing_datasets(filepath: str = "data/known_datasets.json") -> set:
    if os.path.exists(filepath):
        with open(filepath, 'r') as f:
            return set(json.load(f))
    return set()

def save_datasets(datasets: set, filepath: str = "data/known_datasets.json"):
    with open(filepath, 'w') as f:
        json.dump(list(datasets), f, indent=2)

def get_dataset_id(dataset: Dict, platform: str) -> str:
    if platform == "huggingface":
        return f"hf:{dataset.get('id', dataset.get('name', ''))}"
    elif platform == "github":
        return f"gh:{dataset.get('full_name', '')}"
    elif platform == "kaggle":
        return f"kg:{dataset.get('ref', '')}"
    elif platform == "zenodo":
        return f"zd:{dataset.get('id', dataset.get('recid', ''))}"
    elif platform == "roboflow":
        return f"rf:{dataset.get('id', dataset.get('name', ''))}"
    return f"{platform}:{str(dataset)}"

def main():
    searcher = NepaliDatasetSearcher()
    known_datasets = load_existing_datasets()
    new_datasets = []

    all_results = searcher.search_all(limit=50)

    for platform, datasets in all_results.items():
        for ds in datasets:
            ds_id = get_dataset_id(ds, platform)
            if ds_id not in known_datasets:
                known_datasets.add(ds_id)
                new_datasets.append({
                    "id": ds_id,
                    "platform": platform,
                    "name": ds.get('name', ds.get('title', ds.get('ref', 'Unknown'))),
                    "url": ds.get('url', ds.get('html_url', ds.get('links', {}).get('html', '#'))),
                    "date": ds.get('last_modified', ds.get('created_at', ds.get('metadata', {}).get('publication_date', ''))),
                    "description": ds.get('description', '')
                })

    save_datasets(known_datasets)

    if new_datasets:
        message = f"Found {len(new_datasets)} new Nepali datasets!\n\n"
        for ds in new_datasets[:10]:
            message += f"• [{ds['name']}]({ds['url']}) ({ds['platform']})\n"

        with open("data/new_datasets.json", "w") as f:
            json.dump(new_datasets, f, indent=2)

        if os.getenv("SLACK_WEBHOOK"):
            import requests
            payload = {"text": message}
            requests.post(os.getenv("SLACK_WEBHOOK"), json=payload)

        print(message)
    else:
        print("No new datasets found.")

if __name__ == "__main__":
    main()

Dataset Comparison and Selection Tools

Dataset Comparison Table Generator

import pandas as pd
from tabulate import tabulate

def compare_datasets(datasets: List[Dict]) -> pd.DataFrame:
    comparison_data = []

    for ds in datasets:
        comparison_data.append({
            "Name": ds.get("name", "N/A"),
            "Platform": ds.get("platform", "N/A"),
            "Size": ds.get("size", "N/A"),
            "Task": ds.get("task", ds.get("category", "N/A")),
            "License": ds.get("license", "N/A"),
            "Last Updated": ds.get("last_modified", ds.get("date", "N/A")),
            "Downloads": ds.get("downloadCount", ds.get("downloads", "N/A")),
            "Stars": ds.get("stargazers_count", "N/A"),
            "URL": ds.get("url", "#")
        })

    df = pd.DataFrame(comparison_data)
    return df

# Example usage
datasets = [
    {
        "name": "IRIIS-RESEARCH Nepali Text Corpus",
        "platform": "Hugging Face",
        "size": "10.1 GB",
        "task": "Text Corpus",
        "license": "MIT",
        "last_modified": "2024-11-15",
        "downloads": "5,000+",
        "url": "https://huggingface.co/datasets/IRIIS-RESEARCH/Nepali-Text-Corpus"
    },
    {
        "name": "Amit Pant Nepali Speech-to-Text",
        "platform": "Hugging Face",
        "size": "949 MB",
        "task": "ASR",
        "license": "Apache 2.0",
        "last_modified": "2025-02-20",
        "downloads": "2,000+",
        "url": "https://huggingface.co/datasets/amitpant7/nepali-speech-to-text"
    }
]

df = compare_datasets(datasets)
print(tabulate(df, headers='keys', tablefmt='grid', showindex=False))

Dataset Quality Scoring

from datetime import datetime

def score_dataset(dataset: Dict) -> float:
    score = 0.0

    # Platform weight
    platform_weights = {
        "huggingface": 10,
        "github": 8,
        "kaggle": 9,
        "zenodo": 7,
        "roboflow": 8
    }
    score += platform_weights.get(dataset.get("platform", ""), 5)

    # Size weight (logarithmic scale)
    size_str = str(dataset.get("size", "")).lower()
    if "gb" in size_str:
        score += 15
    elif "mb" in size_str:
        score += 10
    elif "kb" in size_str:
        score += 5

    # License weight
    good_licenses = ["mit", "apache", "cc by", "cc0", "bsd", "gpl"]
    license_str = str(dataset.get("license", "")).lower()
    if any(lic in license_str for lic in good_licenses):
        score += 15

    # Recency weight
    date_str = dataset.get("last_modified", dataset.get("date", ""))
    if date_str:
        try:
            date = datetime.strptime(date_str.split("T")[0], "%Y-%m-%d")
            days_old = (datetime.now() - date).days
            if days_old < 30:
                score += 20
            elif days_old < 90:
                score += 15
            elif days_old < 180:
                score += 10
            elif days_old < 365:
                score += 5
        except:
            score += 5

    # Popularity weight
    downloads = dataset.get("downloads", dataset.get("downloadCount", 0))
    if downloads > 1000:
        score += 10
    elif downloads > 500:
        score += 7
    elif downloads > 100:
        score += 5

    stars = dataset.get("stars", dataset.get("stargazers_count", 0))
    if stars > 100:
        score += 10
    elif stars > 50:
        score += 7
    elif stars > 10:
        score += 5

    # Task specificity weight
    task = str(dataset.get("task", "")).lower()
    if task in ["asr", "ocr", "ner", "classification", "translation"]:
        score += 10
    elif task in ["text corpus", "corpus", "general"]:
        score += 5

    # Description quality
    description = dataset.get("description", "")
    if description and len(description) > 100:
        score += 5

    return min(score, 100.0)

# Example
dataset = {
    "name": "IRIIS-RESEARCH Nepali Text Corpus",
    "platform": "huggingface",
    "size": "10.1 GB",
    "task": "Text Corpus",
    "license": "MIT",
    "last_modified": "2024-11-15",
    "downloads": 5000,
    "description": "Largest Nepali corpus from 99 news websites..."
}

quality_score = score_dataset(dataset)
print(f"Quality Score: {quality_score:.1f}/100")

Learning Resources for Dataset Discovery

Tutorials and Guides

  1. Hugging Face Datasets Guide

  2. Kaggle Datasets Guide

  3. GitHub Advanced Search

  4. Roboflow Documentation

  5. Zenodo Help

Video Tutorials

Topic Video Channel
Finding Datasets on Hugging Face How to Find Datasets on Hugging Face Hugging Face
Kaggle Dataset Discovery Finding Datasets on Kaggle Kaggle
GitHub Advanced Search GitHub Search Tips GitHub
Roboflow Dataset Search Finding Datasets on Roboflow Roboflow
Zenodo Dataset Search Using Zenodo for Research Data Zenodo

Books and Courses

  1. "Natural Language Processing with Python"

    • Covers dataset discovery for NLP

  2. "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow"

    • Dataset finding strategies

  3. Fast.ai Practical Deep Learning

  4. Coursera: Data Science Specialization

Tips for Dataset Discovery

Best Practices

  1. Use multiple platforms: No single platform has all datasets
  2. Check dates: Prioritize recent datasets (2024-2026)
  3. Verify licenses: Ensure datasets have clear usage rights
  4. Check quality: Look for datasets with:
    • Clear documentation
    • Proper labeling/annotation
    • Balanced class distribution
    • Large enough size for your task
  5. Join communities: Follow Nepali NLP/Speech/CV communities
  6. Set up alerts: Use Google Alerts, GitHub notifications, etc.
  7. Contribute back: Share datasets you create with the community
  8. Check citations: Look for datasets cited in recent papers
  9. Verify sources: Ensure datasets come from reputable sources
  10. Test before use: Always validate dataset quality before training

Common Pitfalls to Avoid

  1. Ignoring license restrictions: Some datasets have strict usage limits
  2. Not checking data quality: Datasets may have errors, biases, or poor annotations
  3. Overlooking small datasets: Small but high-quality datasets can be valuable
  4. Forgetting to cite: Always cite datasets in your research
  5. Using outdated datasets: Prioritize recent, well-maintained datasets
  6. Not checking for duplicates: Same dataset may appear on multiple platforms
  7. Ignoring metadata: Pay attention to dataset descriptions, statistics, and provenance
  8. Downloading everything: Be selective to save time and storage
  9. Not verifying authenticity: Ensure datasets are from legitimate sources
  10. Forgetting preprocessing: Many datasets need cleaning before use

Hidden Gems

  1. University repositories: Check Nepali university websites (TU, KU, PU, PoU, etc.)
  2. Government open data: https://data.gov.np/
  3. NGO/INGO data: UN, World Bank, ADB, etc. often have Nepal data
  4. Local news websites: Some publish datasets (Kantipur, Annapurna Post, etc.)
  5. Social media groups: Facebook groups for Nepali AI/ML researchers
  6. Academic theses: Nepali university theses often include datasets
  7. Conference proceedings: Check local tech conference presentations
  8. Hackathon outputs: Datasets created during Nepali hackathons
  9. Student projects: GitHub repos from Nepali university students
  10. Personal blogs: Nepali researchers often share datasets on their blogs

Community and Support

Discussion Forums

Platform Link Purpose
Hugging Face Discussions https://discuss.huggingface.co/ General dataset questions
Kaggle Forums https://www.kaggle.com/discussion Dataset-specific discussions
GitHub Discussions Platform-specific Repository discussions
Reddit r/datasets https://www.reddit.com/r/datasets/ Dataset requests
Reddit r/MachineLearning https://www.reddit.com/r/MachineLearning/ ML dataset discussions
Stack Overflow https://stackoverflow.com/ Technical questions

Nepali AI/ML Communities

Community Platform Focus Link
Nepali NLP Discord/Slack NLP research Check GitHub orgs
AI4Nepal Facebook/LinkedIn AI in Nepal AI4Nepal
Nepal AI Society LinkedIn AI community NAIS
Python Nepal Facebook Python and Data Science Python Nepal
Data Science Nepal Facebook Data Science DS Nepal
Kathmandu AI Meetup AI Meetups Kathmandu AI
F1Soft Group AI LinkedIn Enterprise AI F1Soft AI

Newsletters and Blogs

Resource Type Link
Hugging Face Newsletter Weekly Subscribe
Kaggle Newsletter Weekly Subscribe
Towards Data Science Blog Medium
Analytics Vidhya Blog AV
Nepali Tech Blogs Various Search for "Nepali AI blog"
ResearchGate Academic ResearchGate
Academia.edu Academic Academia

Staying Updated

Notification Methods

  1. Google Alerts

  2. GitHub Notifications

    • Watch repositories: IOST-ASCOL/nepali-datasets, pemagrg1/Nepali-Datasets
    • Follow topics: nepali-nlp, nepali-dataset

  3. Hugging Face Notifications

    • Watch datasets: Click "Watch" on Nepali datasets
    • Follow organizations: IRIISNEPAL, etc.

  4. Kaggle Notifications

    • Follow dataset creators
    • Enable email notifications for new datasets

  5. RSS Feeds

  6. Slack/Discord Bots

    • Set up bots to monitor new datasets
    • Use webhooks for notifications

  7. IFTTT/Zapier

    • Create automation: "If new Nepali dataset on HF, then notify me"
    • IFTTT or Zapier

Dataset Tracking Spreadsheet

Create a spreadsheet to track Nepali datasets:

Column Description Example
Name Dataset name IRIIS-RESEARCH Nepali Text Corpus
Platform Where it's hosted Hugging Face
URL Direct link HF Link
Size Dataset size 10.1 GB
Task Primary task Text Corpus
License Usage license MIT
Last Updated Last modification date 2024-11-15
Downloads Number of downloads 5,000+
Stars GitHub stars 45
Quality Score Your quality rating 95/100
Notes Additional comments Largest Nepali corpus
Status Your status Downloaded/To Review/Rejected
Date Added When you found it 2026-08-08

Template: Create your own spreadsheet with these columns

Quick Start Guide

For Beginners: Finding Your First Nepali Dataset

  1. Start with Hugging Face:

  2. Explore Kaggle:

  3. Check GitHub:

  4. Join Communities:

    • Join Nepali NLP Discord/Slack groups
    • Follow #nepali-datasets on Twitter
    • Subscribe to AI4Nepal newsletters

  5. Start Small:

    • Begin with a small dataset (1-10MB)
    • Try a simple task (text classification, sentiment analysis)
    • Gradually move to larger, more complex datasets

For Researchers: Advanced Discovery

  1. Set up automated monitoring using the Python scripts above
  2. Create a dataset tracking system (spreadsheet or database)
  3. Join academic networks (ResearchGate, Academia.edu)
  4. Follow key researchers on GitHub and social media
  5. Attend conferences and network with Nepali researchers
  6. Collaborate on dataset creation with local institutions
  7. Publish your datasets to contribute back to the community

For Developers: API Integration

  1. Use Hugging Face API for programmatic dataset access
  2. Integrate Kaggle API for dataset downloads
  3. Use GitHub API to monitor repository updates
  4. Create dataset discovery tools for your team
  5. Build dataset recommendation systems using embeddings
  6. Automate dataset validation and quality checks
  7. Create dataset versioning systems for reproducibility

Checklist for Dataset Discovery

Weekly Routine

  • Search Hugging Face for new Nepali datasets (language:ne)
  • Check GitHub for new repos (nepali dataset sort:updated)
  • Browse Kaggle for new datasets (nepali)
  • Search Zenodo for academic datasets (nepali dataset type:dataset)
  • Check Roboflow for CV datasets (nepali)
  • Review Reddit/r/datasets for new posts
  • Check Open Data Nepal for government datasets
  • Follow Nepali AI communities on social media
  • Review Google Alerts notifications
  • Update your dataset tracking spreadsheet

Monthly Routine

  • Run automated dataset monitor script
  • Check academic repositories (IEEE, Figshare, Dryad)
  • Review recent arXiv papers for new datasets
  • Search conference proceedings (ACL, EMNLP, NeurIPS, etc.)
  • Check NGO/INGO websites for new data releases
  • Update dataset quality scores
  • Share new findings with community
  • Contribute to dataset aggregators
  • Clean up old/unused datasets
  • Backup your dataset collection

Quarterly Routine

  • Comprehensive search across all platforms
  • Review and update dataset documentation
  • Verify licenses for all tracked datasets
  • Check for dataset updates/versions
  • Validate data quality of key datasets
  • Update search queries based on new trends
  • Contribute new datasets to community collections
  • Write blog post about new findings
  • Present at local meetups
  • Create tutorial using new datasets

Nepali Datasets to Start With

Rank Dataset Platform Task Size Why It's Great Link
1 IRIIS-RESEARCH Nepali Text Corpus Hugging Face Text Corpus 10.1 GB Largest Nepali corpus, 6.4M articles HF
2 Amit Pant Nepali Speech-to-Text Hugging Face ASR 949 MB Combined OpenSLR + Common Voice, cleaned HF
3 Nepali Handwritten Dataset Major Collection GitHub OCR 2.5 GB Comprehensive handwritten text collection GitHub
4 Birat-Poudel Nepali Sign Language Dataset Hugging Face Sign Language 36,000 images Character-level sign language recognition HF
5 Spandyie Nepali News Dataset Hugging Face News Classification Large Cleaned category labels from Baahrakhari HF
6 Ministry of Finance Nepal Corpus Hugging Face Government Text 2015-2024 Official government documents, cleaned HF
7 Nepali Fake News Dataset v1 Hugging Face Fake News Detection 8,838 samples Synthetic but well-labeled HF
8 Nepali Vehicle Dataset Kaggle Object Detection 4,797 images Real-world vehicle images from Nepal Kaggle
9 Nepal Landslide Dataset Zenodo Semantic Segmentation 230 images + masks Geospatial dataset for disaster response Zenodo: 3675410
10 Nepali Transliteral Dataset GitHub Transliteration - Unicode to Latin script mapping GitHub

Dataset Search Guide

Platform-Specific Search Instructions

How to Search Nepali Datasets on Hugging Face

Method 1: Using the Web Interface

  1. Direct Language Filter:

  2. Advanced Search Queries:

    • Use the search bar at the top
    • Combine terms with AND/OR:
      • nepali AND asr - Find ASR datasets
      • nepali OR ne - Broader search
      • language:ne AND task:text-classification - Classification datasets
      • nepali AND (ocr OR vision OR image) - Computer vision datasets
      • nepali AND (ner OR sentiment OR classification) - NLP datasets
      • nepali AND translation - Translation datasets
      • nepali updated:>2024-01-01 - Recently updated datasets

  3. Sorting and Filtering:

    • Sort by: "Most recent", "Most downloads", "Most likes"
    • Filter by: Task type (automatic-speech-recognition, text-classification, etc.)
    • Filter by: License (MIT, Apache, Creative Commons, etc.)
    • Filter by: Size (Small <1GB, Medium 1-10GB, Large >10GB)

  4. Browsing by Task:

Method 2: Using Hugging Face API

from huggingface_hub import HfApi, list_datasets

# Initialize API
api = HfApi()

# List all Nepali datasets
nepali_datasets = api.list_datasets(filter="language:ne")
for ds in nepali_datasets:
    print(f"Name: {ds.id}")
    print(f"Description: {ds.description}")
    print(f"Downloads: {ds.downloads}")
    print(f"Likes: {ds.likes}")
    print(f"Last Modified: {ds.lastModified}")
    print(f"Link: https://huggingface.co/datasets/{ds.id}\n")

# Search with specific query
datasets = api.list_datasets(filter="nepali asr")
for ds in datasets:
    print(ds.id)

# Get dataset details
from datasets import load_dataset_builder
dataset_builder = load_dataset_builder("dataset-name")
print(dataset_builder.info)

Method 3: Using Hugging Face CLI

# Install CLI
pip install huggingface_hub

# Authenticate (optional for public datasets)
huggingface-cli login

# List Nepali datasets
huggingface-cli list datasets --filter nepali

# Search with query
huggingface-cli list datasets --filter "nepali asr"

# Download a dataset
huggingface-cli download ranjitraut/nepal-constitution-dataset

Method 4: Browser Bookmarklets

Create these bookmarklets for quick access:

  1. All Nepali Datasets:

    javascript:window.location.href='https://huggingface.co/datasets?language=ne'

  2. Nepali ASR Datasets:

    javascript:window.location.href='https://huggingface.co/datasets?q=nepali+automatic-speech-recognition&sort=modified'

  3. Nepali NLP Datasets:

    javascript:window.location.href='https://huggingface.co/datasets?q=nepali+(ner+OR+sentiment+OR+classification)&sort=downloads'

  4. Nepali OCR Datasets:

    javascript:window.location.href='https://huggingface.co/datasets?q=nepali+ocr'

  5. Recently Updated Nepali Datasets:

    javascript:window.location.href='https://huggingface.co/datasets?q=nepali+updated:>2024-01-01&sort=modified'

Method 5: Using Dataset Cards

Each dataset on Hugging Face has a dataset card with:

  • Description
  • Dataset structure
  • Usage examples
  • Citation information
  • License

Example: IRIIS-RESEARCH Nepali Text Corpus shows:

  • 10.1 GB size
  • 6.4M articles
  • MIT license
  • Usage code snippets

How to Search Nepali Datasets on GitHub

Method 1: Using GitHub Web Search

  1. Basic Search:

  2. Advanced Search:

    • Use GitHub Advanced Search
    • Fill in:
      • Keywords: nepali dataset
      • Language: Python, Jupyter Notebook, etc.
      • Sort: Recently updated or Most stars

  3. Search Queries:

Query Purpose Example Results
nepali dataset All Nepali dataset repositories Text corpora, OCR datasets, NLP tools
nepali nlp NLP-related repositories Classification, NER, sentiment analysis
nepali corpus Text corpus repositories News datasets, Wikipedia dumps
nepali ocr OCR/handwriting recognition Character datasets, handwritten text
nepali speech Speech/audio datasets ASR datasets, TTS data
nepali computer vision CV datasets Object detection, classification
nepali handwritten Handwriting datasets Character recognition datasets
nepali sign language Sign language datasets Gesture recognition datasets
language:nepali Repos with Nepali as primary language Code written in Nepali
topic:nepali-nlp NLP topic repositories Curated NLP resources
topic:nepali-dataset Dataset topic repositories Dataset collections
topic:nepali-ocr OCR topic repositories Character recognition projects
nepali dataset stars:>10 Popular repositories Well-maintained datasets
nepali dataset pushed:>2024-01-01 Recently created New datasets from 2024-2026
nepali dataset in:readme Datasets mentioned in README Well-documented repos
  1. Using GitHub Topics:

Method 2: Using GitHub API

import requests
import json

# Search repositories
url = "https://api.github.com/search/repositories"
headers = {"Accept": "application/vnd.github.v3+json"}

# Basic search
params = {
    "q": "nepali dataset",
    "sort": "updated",
    "order": "desc",
    "per_page": 50
}
response = requests.get(url, params=params, headers=headers)
repos = response.json()["items"]

for repo in repos:
    print(f"Repository: {repo['full_name']}")
    print(f"Name: {repo['name']}")
    print(f"Description: {repo['description']}")
    print(f"Stars: {repo['stargazers_count']}")
    print(f"Forks: {repo['forks_count']}")
    print(f"Updated: {repo['updated_at']}")
    print(f"URL: {repo['html_url']}")
    print(f"Language: {repo['language']}")
    print("-" * 80)

# Search with language filter
params = {
    "q": "nepali dataset language:python",
    "sort": "stars",
    "per_page": 30
}
response = requests.get(url, params=params, headers=headers)
python_repos = response.json()["items"]

# Search code files
code_url = "https://api.github.com/search/code"
params = {
    "q": "nepali dataset extension:json OR extension:csv OR extension:txt",
    "per_page": 30
}
response = requests.get(code_url, params=params, headers=headers)
code_results = response.json()["items"]

for result in code_results:
    print(f"File: {result['name']}")
    print(f"Repo: {result['repository']['full_name']}")
    print(f"URL: {result['html_url']}")
    print("-" * 80)

Method 3: Using GitHub CLI (gh)

# Install GitHub CLI
# macOS: brew install gh
# Linux: sudo apt install gh
# Windows: winget install --id GitHub.cli

# Authenticate
gh auth login

# Search for repositories
gh search repos "nepali dataset" --sort updated --order desc
gh search repos "nepali nlp" --language python
gh search repos "topic:nepali-dataset"

# View repository details
gh repo view OWNER/REPO

# Clone a repository
gh repo clone ranjitraut/Nepali-Datasets-Collection

# List files in a repository
gh repo view ranjitraut/Nepali-Datasets-Collection --json files

# Search code in repositories
gh search code "nepali dataset" --extension json
gh search code "nepali ocr" --language python

Method 4: Using GitHub Advanced Search Operators

Operator Example Description
in:name nepali in:name Repos with "nepali" in name
in:description dataset in:description nepali Repos with "dataset" and "nepali" in description
in:readme nepali in:readme Repos with "nepali" in README
language: language:python nepali dataset Python repos about Nepali datasets
stars: nepali dataset stars:>50 Repos with >50 stars
forks: nepali dataset forks:>10 Repos with >10 forks
pushed: nepali dataset pushed:>2024-01-01 Repos updated after Jan 1, 2024
created: nepali dataset created:>2024-01-01 Repos created after Jan 1, 2024
user: user:theranjitraut nepali Repos by specific user
org: org:IOST-ASCOL nepali Repos by specific organization
topic: topic:nepali-nlp topic:dataset Repos with specific topics
label: label:nepali label:dataset Issues/PRs with specific labels

Method 5: GitHub Code Search

To find actual dataset files (JSON, CSV, etc.):

  1. Go to https://github.com/search
  2. Click on "Code" tab
  3. Search: nepali dataset extension:json
  4. Or: nepali corpus extension:csv
  5. Or: language:nepali extension:txt

Example searches:

Method 6: Following Nepali Dataset Repositories

Watch these key repositories for updates:

  1. pemagrg1/Nepali-Datasets - Comprehensive list
  2. IOST-ASCOL/nepali-datasets - Curated collection
  3. ghimiresunil/Curated-List-of-Nepali-NLP-Resources - Resource aggregator
  4. rameshhpathak/nepali-nlp-resources - Tools and datasets
  5. amitness/ml-datasets - ML datasets for Nepal

To watch a repository:

  • Go to the repo page
  • Click "Watch" button (top right)
  • Select "Watching" to get notifications

Method 7: GitHub Notifications

Set up notifications for:

  • New repositories matching "nepali dataset"
  • Updates to watched repositories
  • New issues/PRs in relevant repos

Go to https://github.com/watching to manage your watched repositories.

Quick Reference: Best Search Commands

Platform Command/URL Purpose
Hugging Face https://huggingface.co/datasets?language=ne All Nepali datasets
Hugging Face https://huggingface.co/datasets?q=nepali+asr ASR datasets
Hugging Face https://huggingface.co/datasets?q=nepali+ocr OCR datasets
Hugging Face https://huggingface.co/datasets?q=nepali+ner NER datasets
GitHub https://github.com/search?q=nepali+dataset All Nepali dataset repos
GitHub https://github.com/search?q=nepali+nlp NLP repos
GitHub https://github.com/topics/nepali-nlp NLP topic repos
GitHub https://github.com/topics/nepali-dataset Dataset topic repos
Kaggle https://www.kaggle.com/datasets?tags=16979-Nepali All Nepali datasets
Kaggle https://www.kaggle.com/datasets?search=nepali+ocr OCR datasets
Roboflow https://universe.roboflow.com/search?query=nepali All Nepali CV datasets

Search Cheat Sheet

For NLP Tasks:

  • Hugging Face: language:ne AND (ner OR sentiment OR classification OR qa OR summarization)
  • GitHub: nepali AND (nlp OR "natural language" OR corpus OR dataset)
  • Kaggle: nepali AND (nlp OR text OR classification OR sentiment)

For Speech/Audio:

  • Hugging Face: nepali AND (asr OR "speech-to-text" OR tts OR "text-to-speech")
  • GitHub: nepali AND (speech OR audio OR asr OR tts)
  • OpenSLR: Search for "Nepali" or "ne"

For Computer Vision:

  • Hugging Face: nepali AND (ocr OR vision OR image OR object-detection OR classification)
  • GitHub: nepali AND (computer-vision OR cv OR ocr OR "object detection")
  • Roboflow: nepali OR devanagari
  • Kaggle: nepali AND (image OR vision OR ocr OR detection)

For OCR/Handwriting:

  • Hugging Face: nepali AND (ocr OR handwritten OR "handwriting recognition")
  • GitHub: nepali AND (ocr OR handwritten OR character OR recognition)
  • Kaggle: nepali AND (ocr OR handwritten OR character)

For Translation:

  • Hugging Face: nepali AND (translation OR parallel OR "machine translation")
  • GitHub: nepali AND (translation OR parallel OR corpus)
  • Kaggle: nepali AND (translation OR parallel)

For Legal/Government:

  • Hugging Face: nepali AND (legal OR constitution OR act OR law OR government)
  • GitHub: nepali AND (legal OR constitution OR government OR act)
  • Open Data Nepal: Search for specific government datasets

Last Updated: August 8, 2026 Maintained by: Ranjit Raut Contributions welcome! Submit PR to Nepali-Datasets-Collection

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A comprehensive, organized collection of 100+ Nepali datasets across NLP, Computer Vision, Speech, OCR, and more for AI/ML research and development.

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