solvi-ai/decide-base
text-classification model by solvi-ai
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Model card & documentation
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A 150M-parameter ModernBERT-base cross-encoder for solvi typed questions (same format and answer kinds as decide-large), distilled from decide-large for CPU / browser use: 50 ms per question on a CPU (ONNX fp16). Honest summary. On typed questions over JSON states it matches the large model (typed-decisions 54.5%), and its contract evidence is much better than the previous base model (46% vs 23% supporting quotes). On zero-shot choice questions it is not better than the previous base models (Fast Decisions dev 56.3%; L14d 57.3%, GLiNER2.5-Decide 62.9%). Fast Decisions numbers are on the public dev split in our harness (Fastino's official numbers are on a hidden test split). For reference: GLiNER2.5-Decide 62.9% on Fast Decisions dev and 50.3% on typed-decisions; Laya base 36.0% on typed-decisions. Speed (CPU, 4 threads): ONNX fp16, one question with 10 options and 20 words: 50 ms (fp32 46 ms); a question over a long JSON state 170–270…
Read the full model card ↗ · Preview checked 2026-09-28T08:48:02.897Z
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Model overview
solvi-ai/decide-base is a text-classification model repository published by solvi-ai on Hugging Face. The source reports the solvi library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-classification
- Library
- solvi
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 149,611,014
- Architecture
- ModernBertForMaskedLM
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-09-28T06:27:10.000Z
- Last modified
- 2026-09-28T06:27:43.000Z
Compatibility and lineage
Reported languages: en
Reported base models: answerdotai/ModernBERT-base
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.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-28T06:38:00.545Z. Daily imports are snapshots, not real-time monitoring.
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