EnglishFrenchSpanish

Ad


OnWorks favicon

MTEB download for Windows

Free download MTEB Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named MTEB whose latest release can be downloaded as 1.1.1C-MTEB.PL-MTEB,Multi-GPU.zip. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named MTEB 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

Ad


MTEB


DESCRIPTION

Text embeddings are commonly evaluated on a small set of datasets from a single task not covering their possible applications to other tasks. It is unclear whether state-of-the-art embeddings on semantic textual similarity (STS) can be equally well applied to other tasks like clustering or reranking. This makes progress in the field difficult to track, as various models are constantly being proposed without proper evaluation. To solve this problem, we introduce the Massive Text Embedding Benchmark (MTEB). MTEB spans 8 embedding tasks covering a total of 58 datasets and 112 languages. Through the benchmarking of 33 models on MTEB, we establish the most comprehensive benchmark of text embeddings to date. We find that no particular text embedding method dominates across all tasks. This suggests that the field has yet to converge on a universal text embedding method and scale it up sufficiently to provide state-of-the-art results on all embedding tasks.



Features

  • Dataset selection
  • Datasets can be selected by providing the list of datasets
  • You can also specify which languages to load for multilingual/crosslingual tasks
  • You can evaluate only on test splits of all tasks
  • Use a custom model
  • Evaluate on a custom task


Programming Language

Python


Categories

Neural Search

This is an application that can also be fetched from https://sourceforge.net/projects/mteb.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


Free Servers & Workstations

Download Windows & Linux apps

Linux commands

Ad