GameDecider
GameDecider scores English game scenes with an Ettin-400M model. Check private-test limits, abstention coverage, ONNX files and runtime guards.
By Holdout Labs · Hugging Face weight release: 9 Nov 2026
An English game-scene decision model derived from Ettin-400M, with ONNX files and a Python runtime. It scores NPC intent, mood and quest questions, with optional abstention and 42 compiled adapters. The runtime adds option-order averaging and a minor-safety guard; raw ONNX does not include either.
Quick answers
What is GameDecider by Holdout Labs?
GameDecider: An English game-scene decision model derived from Ettin-400M, with ONNX files and a Python runtime.
Who makes GameDecider?
GameDecider: Holdout Labs
Facts
- Inputs
- Text or JSON game scenes; choice with 2 to 32 options, score with 2 to 10 levels, and yes/no
- Limits
- 3,072 state tokens; two-option choices and choices with 11 or more options never abstain under the published profiles
- Package
- 792.5 MB default fp16-weight ONNX file; Python runtime 0.1.0
- Licence
- Apache-2.0; upstream Ettin-400M is MIT
- Scope
- Fictional game situations; the card excludes consequential decisions about real people
Claims and sources
- The maker reports 60.0% accuracy on 2,993 private questions from unseen task families with option-order averaging. Default thresholds cover 66.2% of that set, versus 97.4% of dev questions. The private evaluation sets and training rows are not released. vendor reportedsource
- On an AMD Ryzen 5 3600X, the maker reports warm model p50 0.92 s for one question in a single option order and 1.80 s with default choice-order averaging. The 200 held-out rows have a median 325 tokens. vendor reportedsource
Links
Source: Card and files → Source: Training run record → Source: Data sources → Source: Licence →
Related projects
No related projects are listed in the registry.