Brain-Score Language is a platform to evaluate computational models of language on their match to behavioral and neural
measurements in the domain of language processing. The intent of Brain-Score is to adopt many (ideally all) the
experimental benchmarks in the field for the purpose of model testing, falsification, and comparison. To that end,
Brain-Score operationalizes experimental data into quantitative benchmarks that any model candidate following
the BrainModel interface can be scored on.
See the Documentation for more details.
Brain-Score is made by and for the community. To contribute, please send in a pull request.
This repository is under active development, and should be considered to be in an alpha status. Code is likely to change substantially, without backwards compatibility. Please let us know of any problems by creating an issue.
python -m pip install -e "." # change "." to ".[test]" to include testing dependenciesPlease note that plugins (models, benchmarks, data, and metrics) may require additional dependencies beyond those installed here. Default behavior will install these dependencies directly into the runtime environment.
To avoid conflicts, we encourage either using an environment manager or setting the BS_INSTALL_DEPENDENCIES environment variable to either no or newenv (e.g. export BS_INSTALL_DEPENDENCIES=newenv).
no will leave all dependency installation up to the user, whereas newenv will create a new conda environment for the duration of the run. If you would like to use the newenv option and do not already have conda installed, you can follow the installation instructions here.
Score an existing model on an existing benchmark:
python brainscore_language score --model_identifier='distilgpt2' --benchmark_identifier='Futrell2018-pearsonr'MIT license