TimeNet:用于时序基础模型的开源数据基础设施
TimeNet: Open-source data infrastructure for Temporal Foundation Models

原始链接: https://github.com/OpenTSLM/TimeNet

NoteTimeNet 是一个预发布项目,通过 TimeF 格式和 TimeNet API 统一不兼容的时间序列数据集。TimeF 存储 manifest.json、control.duckdb 和 Parquet/Zarr 值平面。TimeNet 负责查找、构建、下载和加载数据集,而模型训练、推理和评估仍由你选择的框架完成。TimeNet 在线黑客松邀请参与者接入数据集并训练或微调时序 AI 模型。安装使用 uv add 'timenet[cli]'、uv tool install timenet-connectors,然后构建 timenet/hello-world;它从本地注册表加载,无需凭据或网络。仓库包含 timenet 和 timenet-connectors 包。TimeNet 采用 MIT 许可证,但数据集保留其上游许可证。

TimeNet 是一个用于时序基础模型的开源数据基础设施,被称为“时序数据的 ImageNet”。它将分散的时序数据统一到一个层中,支持分类、问答、预测、生成、编辑和对应等任务,并为机器学习框架提供 API。早期实验据报道,在跨多个数据集训练时,OpenTSLM 的 F1 平均提升 14%,SLIP 提升 22%。该项目是许多大学和组织的研究人员共同协作的成果,目前包含一场最高提供 50,000 美元云积分的在线黑客松。
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原文

Find, build, and load time-series datasets through one shared format.

Note

TimeNet is a pre-release project. Its public API and the TimeF format can change before 1.0.

PyPI Docs License: MIT

Time-series datasets use many incompatible layouts. TimeF gives them one storage format. TimeNet provides one API to find, build, download, and load them.

TimeNet handles the data layer. Model training, inference, and evaluation stay in your chosen framework.

TimeNet Online Hackathon

TimeNet Online Hackathon is live. Pick a time-series problem, onboard a dataset in TimeNet format, then train or fine-tune a Temporal AI Model (e.g. OpenTSLM) to explore what it can do. Choose any use case, from forecasting and classification to explanation, reasoning and beyond.

Register here: challenge.timenet.ai

TimeNet needs Python 3.11 or newer.

uv add 'timenet[cli]'
uv tool install timenet-connectors
timenet-build build timenet/hello-world

The build lands in the local registry at ~/.timenet/registry/timenet/hello-world/1.0.0/. Load it with Python:

from timenet import TimeNet

dataset = TimeNet().load("timenet/[email protected]")
dataset.describe()

signal = dataset.records[0].signals[0]
values = signal.to_numpy()

TimeNet() reads the local registry first, and the local registry holds this exact version. So the example works without registry credentials or network access.

See the Get started guide for installation options and a longer example.

TimeNet architecture diagram

A connector converts a raw source into a TimeF version. The version contains:

  • manifest.json, which identifies the dataset and lists its files
  • control.duckdb, which stores the hierarchy and relationships
  • a Parquet or Zarr values plane, which stores Signal values

A registry stores immutable TimeF versions. The client reads a version without importing its connector.

The repository is a uv workspace with two packages:

Package Purpose
timenet The TimeF model, reader, writer, registries, SDK, and consumer CLI.
timenet-connectors Dataset connectors and the timenet-build producer CLI.

Read the architecture guide for the complete design.

TimeNet uses the MIT License.

This license covers the TimeNet code, not the datasets that connectors fetch. Each dataset keeps its upstream license and access terms. Read the dataset licensing guide before redistribution.

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