tasksource/tasksource-jev-nano-v0

text-classification model by tasksource

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A small decision model that picks the best option from a list — fraud routings, intents, topics, sentiments — using token-level late interaction instead of a classifier head. It is LateOn (149M parameters) fine-tuned on 512k real decisions covering three judgment types: picking one option (choice), yes/no questions (noul), and graded scores (score). No teacher model was used. Why this architecture. The situation (state + question) is encoded once into token vectors and reused for every candidate set, while each option is encoded independently. That gives two properties classifier heads don't have: caching the situation across decisions, and outputs that don't depend on option order (verified exactly permutation-equivariant). Larger peers (GLiClass Modern-Large 399M, GLiNER2.5-Multi 287M, Laya-Multilingual 322M) are omitted from…

tasksource/tasksource-jev-nano-v0 on Hugging Face A short preview, not the full document.

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  1. Tasksource-JEV-Nano-v0
  2. How it scores
  3. Compact peers (all under 200M, same 1k samples)
  4. Use it (only public packages)
  5. Citation

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Model overview

tasksource/tasksource-jev-nano-v0 is a text-classification model repository published by tasksource on Hugging Face. The source reports the sentence-transformers library.

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Model facts

Task
text-classification
Library
sentence-transformers
Recent downloads (30 days)
0
Cumulative likes
0
Hugging Face trending score
0
Reported safetensors parameters
149,015,808
Architecture
ModernBertModel
License
apache-2.0
Access
Not gated by Hugging Face
Created
2026-09-28T06:18:43.000Z
Last modified
2026-09-28T06:19:07.000Z

Compatibility and lineage

Reported languages: en

Reported base models: lightonai/LateOn

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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