This is the Windows app named hora whose latest release can be downloaded as horasourcecode.zip. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named hora with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.
- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application and install it.
- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
SCREENSHOTS:
hora
DESCRIPTION:
hora is an open-source high-performance vector similarity search library designed for large-scale machine learning and information retrieval systems. The project focuses on approximate nearest neighbor search, a fundamental technique used in modern AI applications such as recommendation systems, image search, and semantic search engines. Hora implements multiple efficient indexing algorithms that allow systems to rapidly search through high-dimensional vectors produced by machine learning models. These vectors are commonly generated by neural networks to represent images, text, audio, or other data types in a mathematical embedding space. The library is written in Rust and emphasizes performance, safety, and efficient memory management, making it suitable for production-grade applications requiring low latency and high throughput.
Features
- Approximate nearest neighbor search for high-dimensional vectors
- Multiple indexing algorithms for efficient vector similarity retrieval
- High-performance Rust implementation optimized for speed and safety
- Support for large-scale datasets containing millions of embeddings
- Flexible integration into machine learning and search pipelines
- Low-latency query processing for real-time applications
Programming Language
Rust
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/hora-ml.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.