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Scores on benchmarks

Model rank shown below is with respect to all public models.

.440	average_language rank 21 5 benchmarks	.440 0 ceiling best median

.879	neural_language rank 13 4 benchmarks	.879 0 ceiling best median

1.0	Pereira2018-linear rank 1 2 benchmarks	1.0 0 ceiling best median

1.0	Pereira2018.243sentences-linear v1 rank 1	1.0 0 ceiling best median
	Sample stimuli cannot be displayed publicly for this benchmark.

1.0	Pereira2018.384sentences-linear v1 rank 1	1.0 0 ceiling best median
	Sample stimuli cannot be displayed publicly for this benchmark.

.936	Fedorenko2016-linear_pearsonr v3 rank 12	.936 0 ceiling best median
	Sample stimuli cannot be displayed publicly for this benchmark.

.702	Fedorenko2016-ridge_pearsonr v3 rank 15	.702 0 ceiling best median
	Sample stimuli cannot be displayed publicly for this benchmark.

How to use

from brainscore_language import load_model
model = load_model("qwen2.5-3b")
model.start_task(...)
model.start_recording(...)
model.look_at(...)

Model API

Code examples

Brain Encoding Response Generator (BERG)

Through the BERG you can easily generate neural responses to text sentences of your choice using any Brain-Score language model.

For more information on how to use BERG, see the documentation and tutorial.

Benchmarks bibtex

Layer Commitment

No layer commitments found for this model. Older submissions might not have stored this information but will be updated when evaluated on new benchmarks.

Visual Angle

None degrees