datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
IndustryCorpus2_aerospace
IndustryCorpus2: Aerospace
This repository contains the IndustryCorpus2: Aerospace domain subset of BAAI/IndustryCorpus2.
Refer to the parent dataset card for data construction, intended use, limitations,
and licensing details.
Citation
If you use this dataset in your work, please cite IndustryCorpus2:
@misc{shi2024industrycorpus2,
title = {IndustryCorpus2},
author = {Xiaofeng Shi and Lulu Zhao and Hua Zhou and Donglin Hao},
year = {2024}… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryCorpus2_aerospace.IndustryInstruction_Aerospace
IndustryInstruction: Aerospace
This repository contains the IndustryInstruction: Aerospace domain subset of BAAI/IndustryInstruction.
Refer to the parent dataset card for data construction, intended use, limitations,
and licensing details.
Citation
If you use this dataset in your work, please cite IndustryInstruction:
@misc{shi2024industryinstruction,
title = {IndustryInstruction},
author = {Xiaofeng Shi and Lulu Zhao and Hua Zhou and Donglin Hao and… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryInstruction_Aerospace.aerospaceus-airline-aerospace-defense-layoffs-warn-act-notices-daily
US airline, aerospace and defense layoffs — the actual WARN Act filings, rebuilt every day
Last rebuilt: 2026-09-22. 1,548 layoff and closure notices filed by
airlines and regional carriers, airport ground-handling and catering contractors, aircraft and engine makers, avionics and airfoil shops, and defense and space primes and their suppliers with US state labor departments — 307,642 workers,
301 employers, 45 states, 1989–2026.
172 of the notices (11.1%) were recorded by the… See the full description on the dataset page: https://huggingface.co/datasets/APProjects/us-airline-aerospace-defense-layoffs-warn-act-notices-daily.omie-aerospace-qa
Omie Aerospace QA
Small hand-curated set of aerospace engineering Q&A pairs. Built as one of the training sources for Omie, a small from-scratch language model.
83 pairs, single-turn. Covers propulsion basics (Isp, delta-v, staging, engine types, nozzles), orbital mechanics (Hohmann transfers, geostationary orbit, escape velocity), aerodynamics (stall, drag, Mach, sonic booms), reentry/materials (Inconel, ablative heat shields), and flight computer / hobby rocketry stuff (apogee… See the full description on the dataset page: https://huggingface.co/datasets/KerbalMissile/omie-aerospace-qa.aerospace-interpretation-assumption-control-v01Interpretation and Assumption Control v01
What this dataset is
This dataset evaluates whether a system handles incomplete or ambiguous aerospace information without inventing structure.
You give the model:
A partial flight, performance, or guidance task
Incomplete configuration or environmental data
An analysis request that appears reasonable
You ask it to choose a response.
PROCEED
CLARIFY
REFUSE
The correct move is often to stop.
Why this matters
Aerospace failures rarely come from math… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/aerospace-interpretation-assumption-control-v01.Engineering_AerospaceText data related to the subject of Aerospace Engineering.
Compressed file "aerospace-*.tar.gz" is a collection of json files, which are filtered from Fineweb dataset.
The classification was done by fasttext (https://github.com/ZJLab-ZBZX/Data-Processing-Toolkit-for-LLMs/tree/main/Subject_Classifier).
And we randomly selected 2.5% classified data, and checked them by Qwen-2-7B LLM through customized prompt.
The accuracy of the classified data is about 92.86%.
File "stat-aerospace.jsonl"… See the full description on the dataset page: https://huggingface.co/datasets/lzy0928/Engineering_Aerospace.ams_data_train_generic_v0.1_100Question and answer pairs for the first 100 entries of aerospace mechanism symposia 5000 word chunk entries. Full file of entries is here: https://github.com/dsmueller3760/aerospace_chatbot/blob/llm_training/data/AMS/ams_data_answers.jsonl
See this repository for details: https://github.com/dsmueller3760/aerospace_chatbot/tree/main
Prompts generated using TheBloke/Llama-2-7B-Chat-GGUF
RGBD-VideoCount
RGBD-VideoCount
RGBD-VideoCount is an RGB-D video dataset for video object counting in crowded and occluded scenes. It provides synchronized RGB frames and depth maps, together with instance-level annotations for evaluating detection, cross-frame association, and video-level de-duplication.
Dataset Summary
195 RGB-D video clips
6 object categories
2,032 finely annotated frames
77,638 instance bounding boxes
Multi-category shelf and crowded-object scenes
RGB… See the full description on the dataset page: https://huggingface.co/datasets/aerospace123/RGBD-VideoCount.ams_data_train_mistral_v0.1_100Question and answer pairs for the first 100 entries of aerospace mechanism symposia 5000 word chunk entries. Full file of entries is here: https://github.com/dsmueller3760/aerospace_chatbot/blob/llm_training/data/AMS/ams_data_answers.jsonl
See this repository for details: https://github.com/dsmueller3760/aerospace_chatbot/tree/main
Prompts generated using TheBloke/Llama-2-7B-Chat-GGUF
Format representative of mistral's instruct llms:
https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1… See the full description on the dataset page: https://huggingface.co/datasets/ai-aerospace/ams_data_train_mistral_v0.1_100.somosnlp-2026-aerospace
Dataset Card: Conjunto de Datos Aeroespacial y Cultural Completo
Resumen del Dataset
Este conjunto de datos ha sido diseñado específicamente para la evaluación cultural, lingüística y de alineación de Modelos de Lenguaje (LLMs) en el ámbito iberoamericano, con un foco especial en la historia aeroespacial, técnica, científica e histórica.
Contiene 1.716 interacciones de tipo conversacional (multi-turn) distribuidas en múltiples países de habla hispana y portuguesa.… See the full description on the dataset page: https://huggingface.co/datasets/somosnlp-hackathon-2026/somosnlp-2026-aerospace.regime-phase-recognition-aerospace-v01Regime and Phase Recognition v01
What this dataset is
This dataset evaluates whether a system recognizes when the governing aerospace regime or flight phase has changed.
You give the model:
Vehicle class and example
Speed or Mach number
Altitude and atmospheric context
Angle of attack or maneuver
A stated modeling assumption
You ask one question.
Are the same rules
still valid here
Why this matters
Aerospace failures often occur at boundaries.
Common failure patterns:
Treating transonic flow… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/regime-phase-recognition-aerospace-v01.ac-text-embedding-ada-002-ams-testpurple-aerospace-mix-v2-300-18purple-aerospace-mix-v2-300-96purple-aerospace-mix-v1-80-24purple-aerospace-mix-v1-80-80purple-aerospace-mix-v1-80-128ams_data_full_2000-2020Aerospace Mechanism Symposia PDF documents parsed by page. All symposia documents from the year 2000-2022 are included. No splitting was used.
Original documents here: https://github.com/dan-s-mueller/aerospace_chatbot/tree/main/data/AMS
purple-aerospace-mix-v2-200-26purple-aerospace-mix-v1-80-4purple-aerospace-mix-v1-80-10purple-aerospace-mix-v1-80-102purple-aerospace-mix-v2-300-20purple-aerospace-mix-v2-300-64purple-aerospace-mix-v1-80-28purple-aerospace-mix-v1-80-256purple-aerospace-mix-v1-80-432purple-aerospace-mix-v2-300-24purple-aerospace-mix-v2-300-28