This is the Windows app named Hiera whose latest release can be downloaded as v0.1.4_CodeLicenseisnowApache2.0!sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Hiera 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。
截图:
希拉
描述:
Hiera is a hierarchical vision transformer designed to be fast, simple, and strong across image and video recognition tasks. The core idea is to use straightforward hierarchical attention with a minimal set of architectural “bells and whistles,” achieving competitive or superior accuracy while being markedly faster at inference and often faster to train. The repository provides installation options (from source or Torch Hub), a model zoo with pre-trained checkpoints, and code for evaluation and fine-tuning on standard benchmarks. Documentation emphasizes that model weights may have separate licensing and that the code targets practical experimentation for both research and downstream tasks. Community discussions cover topics like dataset pretrains, integration in other frameworks, and comparisons with related implementations. Security and contribution guidelines follow Meta’s open-source practices, and activity shows ongoing interest and usage across the community.
功能
- Hierarchical attention transformer architecture
- High-throughput inference with strong accuracy
- Model zoo with ready-to-use checkpoints
- Training and fine-tuning scripts for common benchmarks
- Torch Hub and source installation paths
- Active community discussions and issue tracking
程式语言
Python
分类
This is an application that can also be fetched from https://sourceforge.net/projects/hiera.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.