"Seq vs Seq: An Open Suite of Paired Encoders and Decoders": the first collection of encoder-only and decoder-only models trained from scratch with identical data, architecture, and recipe — six sizes from 17M to 1B, each in both flavors, on 2T tokens of open data (DCLM, Dolma v1.7, code, scientific papers). A clean testbed for the encoder-vs-decoder question: encoders win MNLI even against larger decoders, decoders win generation, and cross-objective continued training doesn't close the gap. JHU-CLSP (Weller et al.), MIT-licensed with released data and checkpoints.

Model Details

Architecture DENSE
Parameters 1B
Training tokens 2T
License MIT

Variants

Name Parameters Notes
Ettin 17M 17M
Ettin 32M 32M
Ettin 68M 68M
Ettin 150M 150M
Ettin 400M 400M
Ettin 1B 1B

Paper

open-weightpretrainingresearch

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