Codesota · Models · ST-MoE-32BGoogle Brain2 results · 2 benchmarks
Model card

ST-MoE-32B.

Google Brainopen-sourceUnknown paramsSparse Mixture-of-Experts Transformer

Stable and transferable sparse expert model. SuperGLUE SOTA in 2022.

§ 01 · Benchmarks

Every benchmark ST-MoE-32B has a recorded score for.

#BenchmarkArea · TaskMetricValueRankDateSource
01SuperGLUENatural Language Processing · Text Classificationaverage-score91.2%#2/72022-02-17source ↗
02GLUENatural Language Processing · Text ClassificationSuperGLUE avg91.2%#2/52022-02-01source ↗
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 02 · Strengths by area

Where ST-MoE-32B actually performs.

Natural Language Processing
2
benchmarks
avg rank #2.0
§ 03 · Papers

2 papers with results for ST-MoE-32B.

  1. 2022-02-17· Natural Language Processing· 1 result

    ST-MoE: Designing Stable and Transferable Sparse Expert Models

  2. 2022-02-17· 1 result

    ST-MoE: Designing Stable and Transferable Sparse Expert Models

§ 04 · Related models

Other Google Brain models scored on Codesota.

CoAtNet-7
0 results
§ 05 · Sources & freshness

Where these numbers come from.

arxiv
2
results
2 of 2 rows marked verified. · first result 2022-02-01, latest 2022-02-17.