This is the Windows app named Granite TSFM whose latest release can be downloaded as v0.3.1sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Granite TSFM with OnWorks for free.
请按照以下说明运行此应用程序:
- 1. 在您的 PC 中下载此应用程序。
- 2. 在我们的文件管理器 https://www.onworks.net/myfiles.php?username=XXXXX 中输入您想要的用户名。
- 3. 在这样的文件管理器中上传这个应用程序。
- 4. 从本网站启动任何 OS OnWorks 在线模拟器,但更好的 Windows 在线模拟器。
- 5. 从您刚刚启动的 OnWorks Windows 操作系统,使用您想要的用户名转到我们的文件管理器 https://www.onworks.net/myfiles.php?username=XXXXX。
- 6. 下载应用程序并安装。
- 7. 从您的 Linux 发行版软件存储库下载 Wine。 安装后,您可以双击该应用程序以使用 Wine 运行它们。 您还可以尝试 PlayOnLinux,这是 Wine 上的一个花哨界面,可帮助您安装流行的 Windows 程序和游戏。
Wine 是一种在 Linux 上运行 Windows 软件的方法,但不需要 Windows。 Wine 是一个开源的 Windows 兼容层,可以直接在任何 Linux 桌面上运行 Windows 程序。 本质上,Wine 试图从头开始重新实现足够多的 Windows,以便它可以运行所有这些 Windows 应用程序,而实际上不需要 Windows。
SCREENSHOTS
Ad
Granite TSFM
商品描述
granite-tsfm collects public notebooks, utilities, and serving components for IBM’s Time Series Foundation Models (TSFM), giving practitioners a practical path from data prep to inference for forecasting and anomaly-detection use cases. The repository focuses on end-to-end workflows: loading data, building datasets, fine-tuning forecasters, running evaluations, and serving models. It documents the currently supported Python versions and points users to where the core TSFM models are hosted and how to wire up service components. Issues and examples in the tracker illustrate common tasks such as slicing inference windows or using pipeline helpers that return pandas DataFrames, grounding the library in day-to-day time-series operations. The ecosystem around TSFM also includes a community cookbook of “recipes” that showcase capabilities and patterns. Overall, the repo is designed as a hands-on companion for teams adopting time-series foundation models in production-leaning settings.
功能
- Notebooks and scripts for training, evaluation, and serving
- Pipeline helpers that operate on pandas-friendly data structures
- Guidance to hosted TSFM model weights and service components
- Examples addressing windowing, slicing, and inference workflows
- Compatibility across modern Python versions (3.10–3.12)
- Community cookbook with practical time-series “recipes”
程式语言
Python
分类
This is an application that can also be fetched from https://sourceforge.net/projects/granite-tsfm.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.