solvi-ai/decide-large

text-classification model by solvi-ai

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A 396M-parameter ModernBERT-large cross-encoder that answers typed questions about a text or a JSON state for solvi: one option, several options, ordered scores, yes / no, not stated, spans, evidence quotes, rankings and numbers (bins), with a calibrated confidence and an act / escalate signal per answer. Same format as the 150M decide-base (solvidecide v2, subformat l14g typed v2); this is the larger, stronger variant. Honest summary. It is clearly better than our previous deciders on every test, and better than GLiNER2.5-Decide on typed questions over JSON states — but it does not beat GLiNER2.5-Decide on zero-shot choice questions (Fast Decisions dev 59.4% vs 62.9%). With 64 labelled examples per head it reaches 63.0%. It is also slower: 137 ms per question on a CPU (ONNX fp16). Criteria were registered before training (research log L19; 4 of 10 met for this model — the misses are under Limitations). The Fast…

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  1. solvi-ai/decide-large (preview)
  2. Results (held-out tests; never used for training or checkpoint selection)
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  4. Training data and attribution
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Model overview

solvi-ai/decide-large is a text-classification model repository published by solvi-ai on Hugging Face. The source reports the solvi library.

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Model facts

Task
text-classification
Library
solvi
Recent downloads (30 days)
0
Cumulative likes
0
Hugging Face trending score
0
Reported safetensors parameters
395,839,494
Architecture
ModernBertForMaskedLM
License
apache-2.0
Access
Not gated by Hugging Face
Created
2026-09-28T06:27:45.000Z
Last modified
2026-09-28T06:29:13.000Z

Compatibility and lineage

Reported languages: en

Reported base models: answerdotai/ModernBERT-large

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Source: Hugging Face Hub. Metadata observed 2026-09-28T06:38:00.545Z. Daily imports are snapshots, not real-time monitoring.

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