datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Timeseries-QA
Timeseries-QA
This is a dataset for Timeseries Instruction Tuning.
It was created using the following steps:
Extracted features from time series data in AutonLab/Timeseries-PILE
microsoft/Phi-3-medium-4k-instruct generated the QA pairs
Timeseries Instruction Tuning用のデータセットです。
以下の手順で作成しました。
AutonLab/Timeseries-PILE の時系列データの特徴を抽出
microsoft/Phi-3-medium-4k-instruct がQAを作成
Dataset Details
Dataset Description
Curated by: HachiMLLanguage(s) (NLP): English… See the full description on the dataset page: https://huggingface.co/datasets/HachiML/Timeseries-QA.time-series-language-alignment
TS-Insights Dataset
Dataset Description
TS-Insights is the official dataset for the paper "Insight Miner: A Time Series Analysis Dataset for Cross-Domain Alignment with Natural Language". This work is done by Project Mineral from Google X in 2023.
It is the first large-scale general-domain dataset designed to align time-series data with natural language descriptions. The dataset supports the training of Large Multimodal Models (LMMs) to understand time series as a new… See the full description on the dataset page: https://huggingface.co/datasets/zhykoties/time-series-language-alignment.time-series-foundation-models-papers
Time Series Foundation Models Papers — FineSet
A research-paper dataset on Time Series Foundation Models Papers, assembled, deduplicated, and quality-scored by
FineSet from arXiv and Semantic Scholar.
📸 This is a dated snapshot — generated 2026-06-19.
It is not auto-updated. Research on Time Series Foundation Models Papers moves fast — new papers land on arXiv every
week. Want this same dataset refreshed daily, on a topic you choose? See the bottom. ↓
Why this… See the full description on the dataset page: https://huggingface.co/datasets/fineset-io/time-series-foundation-models-papers.Wearable_TimeSeries_HealthRecommendation_Dataset
Wearable Time-Series Health Intervention Dataset
数据集概述
本数据集用于训练大语言模型，使其能够根据穿戴设备时间序列异常检测结果，生成符合 P3 与 PROCEED 框架的个性化健康干预方案。
数据集信息
数据集名称: Wearable_TimeSeries_HealthRecommendation_Dataset
数据格式: JSONL (每行一个 JSON 对象)
数据量: 87 条训练样本
字符数: 约 481,245 字符
用途: 监督微调 (SFT) 训练
数据格式
每条数据采用 ChatML 格式，包含以下结构：
{
"messages": [
{
"role": "system",
"content": "系统提示词，定义模型角色和输出要求"
},
{
"role": "user"… See the full description on the dataset page: https://huggingface.co/datasets/oscarzhang/Wearable_TimeSeries_HealthRecommendation_Dataset.