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Strands-Decider E4B Gemma4 v1 2610
A Strands decider v1 checkpoint: a LoRA adapter and readout head on google/gemma-4-E4B-it that answers typed decisions with calibrated confidence; its model-index reports 0.8095 JevBench public accuracy (187/231) and mixed code-bug evaluation scores.
- Reading time
- 2 min
- Published by
- Community
- Author
- Strands Agents
- Last verified
- Oct 2026
- Capabilities
- Open sourceSelf-hostedRuns locally
Highlights
- LoRA adapter plus a small readout head on google/gemma-4-E4B-it; the model-index reports 0.8095 JevBench public accuracy (187/231).
- Reports Musique 0.922, ContractNLI 0.872, boardgame 0.844, hotpotqa 0.829 and held-out short tasks 0.684 (n=6000).
- Code evals range from commit_message 0.989 and docstring_match 0.955 to correct_solution 0.371, each on 89 items.
- Trained on public datasets including HelpSteer2, commitpackft, cubert_ETHPy150Open and code_contests; Apache-2.0 adapter.
Watch out
Card reviewed 2026-10-17; the repository has no prose card, so this entry rests on the front matter and self-reported model-index results rather than an independent evaluation. The adapter declares Apache-2.0 while the gemma-4-E4B-it base keeps Google's Gemma terms.
Questions about this entry
Short answers drawn from the linked project or page.
A v1 checkpoint of the Strands decider family: a LoRA adapter plus a small readout head on google/gemma-4-E4B-it that scores the options of typed questions with calibrated confidence instead of generating text.
JevBench public at 4096-token serving 0.8095 (187/231) and a list of publisher eval configs: held-out short tasks 0.684 (n=6000), boardgame 0.844, ContractNLI 0.872, hotpotqa 0.829 and Musique 0.922.
Mixed: commit_message 0.989, docstring_match 0.955, cwe_choice 0.933 and bug_swapped_operands 0.843, but correct_solution 0.371 and bug_wrong_binary_operator 0.719, each measured on 89 items.
It is an adapter on google/gemma-4-E4B-it, declared Apache-2.0 in the repository front matter, while the Gemma base keeps Google's own Gemma terms, so check both before commercial use.
Like the rest of the family it answers typed decision questions (choice, noul, score) with probabilities rather than text, following the System One style the Strands decider line targets; this card itself carries no API or serving notes.
Same recipe on a smaller base: the E2B uses google/gemma-4-E2B-it and reports 0.7792 JevBench (180/231) and 0.652 short-task accuracy, against this model's 0.8095 and 0.684.
No. The repository holds front matter and model-index results only, with no prose usage notes or commands, so serving specifics would have to come from the wider Strands decider codebase, which this card does not link.
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