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Open-weight model · Text classification
by DataAgent DataAgent/Quorum-Reader-Qwen3-4B-Adapter
Quorum-Reader-Qwen3-4B-Adapter is a model for text classification from DataAgent, released under Apache License 2.0 (access requested at publisher). Its published files total 528.6 MB.
A LoRA adapter for Qwen/Qwen3-4B — the in-context reader of the Quorum 24-shot intent-classification ensemble. Given 24 retrieved examples in the prompt (no weight update), it scores every candidate label in a single forward pass.
By DataAgent, published under apache-2.0, revision e0765b768e04.
A LoRA adapter for Qwen/Qwen3-4B — the in-context reader of the Quorum 24-shot intent-classification ensemble. Given 24 retrieved examples in the prompt (no weight update), it scores every candidate label in a single forward pass. Combined (geometric mean) with a frozen BAAI/bge-large-en-v1.5 nearest-neighbour over the same 24 examples, the ensemble reaches 0.932 on Banking77 (full 3,080 test) — above the closed API Jev's 0.924 at Jev's own 24-shot protocol. In our study a further configuration (per-class descriptions + a calibration-selected combination) reached 0.938 and significantly beat Jev on a paired McNemar test LoRA (r = 64) on Qwen/Qwen3-4B, fine-tuned on a mixture of public…
A LoRA adapter for Qwen/Qwen3-4B — the in-context reader of the
Quorum 24-shot intent-classification ensemble.
Given 24 retrieved examples in the prompt (no weight update), it scores every candidate label in a single
forward pass. Combined (geometric mean) with a frozen BAAI/bge-large-en-v1.5 nearest-neighbour over the same
24 examples, the ensemble reaches 0.932 on Banking77 (full 3,080 test) — above the closed API Jev's 0.924
at Jev's own 24-shot protocol. In our study a further configuration (per-class descriptions + a
calibration-selected combination) reached 0.938 and significantly beat Jev on a paired McNemar test
(p = 0.0014).
LoRA (r = 64) on Qwen/Qwen3-4B, fine-tuned on a mixture of public intent-classification datasets with
Banking77 held out. Single-forward answer-token option scoring.
# https://github.com/DataAgent-Lab/Quorum
python scripts/eval_24shot.py --dataset banking77 --adapter DataAgent/Quorum-Reader-Qwen3-4B-Adapter
Adapter weights: Apache-2.0. The base model and datasets retain their own licenses.
4 files, 528.6 MB in total. The weights are 1 file totalling 528.6 MB in safetensors.
| File | Type | Size | SHA-256 |
|---|---|---|---|
| adapter_model.safetensors | Weights | 528.6 MB | — |
| adapter_config.json | Configuration | 1.2 KB | — |
| README.md | Documentation | 2.1 KB | — |
| .gitattributes | Repository | 1.5 KB | — |
DataAgent grants access through its official repository on Hugging Face. Read the license.
| Precision | Weights in memory |
|---|---|
| As published | 528.6 MB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Yes. Quorum-Reader-Qwen3-4B-Adapter is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.
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