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Gopher family 44M
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Gopher family 44M is a closed-weights language model from Google DeepMind, released December 2021. Its published size is 0.044B parameters. Licence: proprietary.
Catalogue identity notes
Smallest siblings of Gopher 280B trained by DeepMind on MassiveText (Rae et al., arXiv:2112.11446, Table 1). Never released. Comparison-only.
Model information sources
Score within the LAMBADA (OpenAI version), last-word accuracy comparison set only.
$ how it compares
Scored LLMs released closest to Gopher family 44M, out of 1182 with a score.
| # | model | score | where |
|---|---|---|---|
| 1034 | 34±1 | never released | |
| 1035 | 34±1 | comparison only | |
| 1106 | 27±1 | never released | |
| 1156 | 12±2 | never released | |
| 1158 | 12±1 | comparison only |
$ what it's good at
other tests1 not in a task · 81% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LAMBADA (OpenAI version), last-word accuracy lab | 30.1% ✎ | █··█·█··█·██ beats 0/5 | 81% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · Scaling Language Models: Meth… 81%
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
| source | results | share of the score |
|---|---|---|
| 1 | 81% | |
| prior · pull toward the middle | 19% | |
| weighted average | = 30.7 |
$ improve this page
Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json