Berk/assay-compiled-base
text-classification model by Berk
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A small-tier decision model from the Assay project: typed questions (bool, choice, score) over a state produce calibrated probability distributions with an evidence signal, and no text is generated. It is the small, CPU-friendly tier, with no language model at all. The decoder models (Berk/assay-4b, Berk/assay-27b) are more accurate and larger. It runs on a CPU, and it abstains. 149M parameters, 29 ms per decision without a GPU. On tasks it has never seen it acts on 8% of bool questions at a 5.0% error rate and hands the rest over rather than guessing -- a conformal prediction set against a fitted error rate, not a threshold on a softmax someone eyeballed. It abstains far more than the decoder tiers because it is far smaller; that is the trade, and it is visible instead of hidden. Accuracy on those unseen tasks is 0.606. If you have a GPU, start with…
Read the full model card ↗ · Preview checked 2026-11-03T14:41:49.162Z
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Model overview
Berk/assay-compiled-base is a text-classification model repository published by Berk on Hugging Face. A library was not reported.
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Model facts
- Task
- text-classification
- Library
- Not reported
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 149,014,272
- Architecture
- ModernBertModel
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-09-22T06:32:29.000Z
- Last modified
- 2026-09-22T06:34:52.000Z
Compatibility and lineage
Reported languages: en
Reported base models: Alibaba-NLP/gte-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.
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-22T06:37:17.952Z. Daily imports are snapshots, not real-time monitoring.
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