alice-noa-chan/ayaka-large
text-classification model by alice-noa-chan
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Model card & documentation
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Ayaka large is an open, MIT-licensed decision model for Jev-style structured decisions. You give it a state and typed questions (noul / choice / score), and it returns a calibrated probability for every candidate label. It is a LoRA adapter plus a small decision head on google/gemma-4-12B-it (text stack only, base revision 707f0a3b8a3c7ad586ed01e27eafbad8a27dd0f7). It is trained only on license-clean data. Code, training pipeline and documentation: JevBench public tiers. The single-pass p50 is on an A100, one request at a time. \ Measured through the HTTP server. Routed hard questions take about 10 s. Choose large for accuracy, and small or base when latency, memory or cost matter more. All share the same code, training data, prompt format, server and API. They differ in backbone size, LoRA rank (r64 for large, r32 for base and small) and training length (860 steps for large, 1,200 for base and small). The worked-steps route…
Read the full model card ↗ · Preview checked 2026-11-13T22:33:12.834Z
Inside the original model card — Document outline
- Ayaka large
- Ayaka family
- Other Ayaka models
- Use (pinned)
- Worked-steps route (--reasoning)
- Results (JevBench public tiers)
- Latency
- Tokens and cost per decision
- Training
- Training data (35 sources)
- Benchmark disclosure
- License
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Documentation belongs to its respective authors. Reported project/model license: mit. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
alice-noa-chan/ayaka-large is a text-classification model repository published by alice-noa-chan on Hugging Face. The source reports the ayaka 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
- ayaka
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2026-09-28T05:52:34.000Z
- Last modified
- 2026-09-28T05:59:35.000Z
Compatibility and lineage
Reported languages: en, ko, ja
Reported base models: google/gemma-4-12B-it
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.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.