Skip to main content

Scandinavian Embedding Benchmark

Project description

Scandinavian Embedding Benchmark

PyPI Python Version documentation Tests Ruff DOI

A benchmark for evaluating sentence/document embeddings of Scandinavian language models.

Installation

You can install the Scandinavian Embedding Benchmark (seb) via pip from PyPI:

pip install seb

To see more examples, see the documentation.

📖 Documentation

Documentation
🔧 Installation Installation instructions on how to install this package
👩‍💻 Usage Introduction on how to use the package
📖 Documentation A minimal and developing documentation

💬 Where to ask questions

Type
🚨 Bug Reports GitHub Issue Tracker
🎁 Feature Requests & Ideas GitHub Issue Tracker
👩‍💻 Usage Questions GitHub Discussions
🗯 General Discussion GitHub Discussions

Citation

To cite this work please refer to the following article:

Enevoldsen, K., Kardos, M., Muennighoff, N., & Nielbo, K. (2024). The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding. https://openreview.net/forum?id=pJl_i7HIA72

or use the following BibTeX:

@misc{enevoldsen2024scandinavian,
      title={The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding}, 
      author={Kenneth Enevoldsen and Márton Kardos and Niklas Muennighoff and Kristoffer Laigaard Nielbo},
      year={2024},
      eprint={2406.02396},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

seb-0.13.7.tar.gz (2.2 MB view details)

Uploaded Source

Built Distribution

seb-0.13.7-py3-none-any.whl (715.3 kB view details)

Uploaded Python 3

File details

Details for the file seb-0.13.7.tar.gz.

File metadata

  • Download URL: seb-0.13.7.tar.gz
  • Upload date:
  • Size: 2.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for seb-0.13.7.tar.gz
Algorithm Hash digest
SHA256 ea97468c898731a58ea6218d645e232c3f0790207d8a77c9ad7dab0a0af4e873
MD5 ebaa3c8d90ee91c0339d6c5cfe3ee91f
BLAKE2b-256 85d84209f6ef855c721dab35f3aa0035c02e641ccbc33e114178ec3b9d324b28

See more details on using hashes here.

Provenance

The following attestation bundles were made for seb-0.13.7.tar.gz:

Publisher: release.yml on KennethEnevoldsen/scandinavian-embedding-benchmark

Attestations:

File details

Details for the file seb-0.13.7-py3-none-any.whl.

File metadata

  • Download URL: seb-0.13.7-py3-none-any.whl
  • Upload date:
  • Size: 715.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for seb-0.13.7-py3-none-any.whl
Algorithm Hash digest
SHA256 bc6ed5e9d24053c7a39168c804539cfbb0961b6e428b1a48d0c60b2ac3f25aed
MD5 68c44620802b402d3ee01c6b42a205a4
BLAKE2b-256 108da67478e5434c005a1c47a08caeca0c401d55fbb806d6dbdcc28050ae521d

See more details on using hashes here.

Provenance

The following attestation bundles were made for seb-0.13.7-py3-none-any.whl:

Publisher: release.yml on KennethEnevoldsen/scandinavian-embedding-benchmark

Attestations:

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page