datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
cqadupstack-programmers
CQADupstackProgrammersRetrieval
An MTEB dataset
Massive Text Embedding Benchmark
CQADupStack: A Benchmark Data Set for Community Question-Answering Research
Task category
t2t
Domains
Programming, Written, Non-fiction
Referencehttp://nlp.cis.unimelb.edu.au/resources/cqadupstack/
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-programmers.cqadupstack-programmers-top-20-gen-queries
NFCorpus: 20 generated queries (BEIR Benchmark)
This HF dataset contains the top-20 synthetic queries generated for each passage in the above BEIR benchmark dataset.
DocT5query model used: BeIR/query-gen-msmarco-t5-base-v1
id (str): unique document id in NFCorpus in the BEIR benchmark (corpus.jsonl).
Questions generated: 20
Code used for generation: evaluate_anserini_docT5query_parallel.py
Below contains the old dataset card for the BEIR benchmark.
Dataset Card for BEIR… See the full description on the dataset page: https://huggingface.co/datasets/income/cqadupstack-programmers-top-20-gen-queries.sfia-9-scraped
SFIA-9-Scraped Dataset
This repository contains the SFIA-9-Scraped dataset, a JSON collection of the Skills Framework for the Information Age (SFIA) version 9 categories and levels, scraped for non-commercial research use.
🚀 Dataset Overview
Name: SFIA-9-Scraped
Hugging Face: Programmer-RD-AI/sfia-9-scraped
DOI: 10.57967/hf/5746
Author: Ranuga Disansa Gamage
Revision: 89feeb8
Publisher: Hugging Face
Year: 2025
Use this dataset to build RAG systems, taxonomy-driven… See the full description on the dataset page: https://huggingface.co/datasets/Programmer-RD-AI/sfia-9-scraped.cqadupstack-programmers-fa
Dataset Summary
CQADupstack-programmers-Fa is a Persian (Farsi) dataset developed for the Retrieval task, with a focus on duplicate question detection in community question-answering (CQA) platforms. This dataset is a translated version of the "Programmers" (Software Engineering) StackExchange subforum from the English CQADupstack collection and is part of the FaMTEB benchmark under the BEIR-Fa suite.
Language(s): Persian (Farsi)
Task(s): Retrieval (Duplicate Question Retrieval)… See the full description on the dataset page: https://huggingface.co/datasets/MCINext/cqadupstack-programmers-fa.aurora_programmer_data
My Awesome Dataset
A comprehensive description of my awesome dataset.
Dataset Description
This dataset contains images of cats and dogs. The images were collected from [mention data source(s), e.g., a specific website, scraped from the internet]. It is intended for use in image classification tasks. The dataset consists of [number] images, with approximately [percentage]% allocated to the training set and [percentage]% to the test set. [Add more details about the… See the full description on the dataset page: https://huggingface.co/datasets/naimulislam/aurora_programmer_data.national-greenhouse-accounts-factors-2024
National Greenhouse Accounts Factors 2024 (Australia)
This dataset contains Australian greenhouse gas emission factors for electricity and gas consumption, structured in JSON format for easy programmatic access. The data is derived from the official Australian Government publication.
Dataset Description
The dataset includes emission factors used to calculate greenhouse gas emissions from:
Electricity consumption by state/territory (Scope 2 and Scope 3)
Gas consumption by… See the full description on the dataset page: https://huggingface.co/datasets/Programmer-RD-AI/national-greenhouse-accounts-factors-2024.MNLP_M3_mcqa_datasetreddit-ProgrammerHumor-testMNLP_M2_mcqa_datasetsfia-9-chunks
sfia-9-chunks Dataset
Overview
The sfia-9-chunks dataset is a derived dataset from sfia-9-scraped. It uses sentence embeddings and hierarchical clustering to split each SFIA-9 document into coherent semantic chunks. This chunking facilitates more efficient downstream tasks like semantic search, question answering, and topic modeling.
Chunking Methodology
We employ the following procedure to generate chunks:
from sentence_transformers import… See the full description on the dataset page: https://huggingface.co/datasets/Programmer-RD-AI/sfia-9-chunks.