Skip to main content

In-loop evaluation tasks for language modeling

Project description

OLMo-in-loop-evals

Code for in-loop evaluation tasks used by the OLMo training team.

Installation

pip install ai2-olmo-eval

Release process

Steps

  1. Update the version in src/olmo_eval/version.py.

  2. Run the release script:

    ./src/scripts/release.sh
    

    This will commit the changes to the CHANGELOG and version.py files and then create a new tag in git which will trigger a workflow on GitHub Actions that handles the rest.

Fixing a failed release

If for some reason the GitHub Actions release workflow failed with an error that needs to be fixed, you'll have to delete the tag on GitHub. Once you've pushed a fix you can simply repeat the steps above.

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

ai2_olmo_eval-0.9.0.tar.gz (85.3 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ai2_olmo_eval-0.9.0-py3-none-any.whl (85.6 MB view details)

Uploaded Python 3

File details

Details for the file ai2_olmo_eval-0.9.0.tar.gz.

File metadata

  • Download URL: ai2_olmo_eval-0.9.0.tar.gz
  • Upload date:
  • Size: 85.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.19

File hashes

Hashes for ai2_olmo_eval-0.9.0.tar.gz
Algorithm Hash digest
SHA256 a36d1210b921aabfbcefc3ecb704a7ac25adf25ae91f1c86343eff2bc142c6cb
MD5 b2325a7dd529840cbe673fb799993574
BLAKE2b-256 29d4019f23e572ffe26afb1607e2e2a82d3f1606d9154136381738489d157d4c

See more details on using hashes here.

File details

Details for the file ai2_olmo_eval-0.9.0-py3-none-any.whl.

File metadata

  • Download URL: ai2_olmo_eval-0.9.0-py3-none-any.whl
  • Upload date:
  • Size: 85.6 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.19

File hashes

Hashes for ai2_olmo_eval-0.9.0-py3-none-any.whl
Algorithm Hash digest
SHA256 61b08ab60ca5b4d175f78c8da95c362c1d745b1502b87de01f437fac768e1cbe
MD5 504404a8c06768a3f0bafa3ae0f645ff
BLAKE2b-256 1667b7307cb86a5d46d34d39461c1232544c7ae4e575a12fd55cde866355399f

See more details on using hashes here.

Supported by

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