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Qwen3-Reranker-0.6B-W4A16-G128
boboliu/Qwen3-Reranker-0.6B-W4A16-G128
Qwen3-Reranker-0.6B-W4A16-G128 is a text classification model from boboliu. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
GPTQ Quantized Qwen/Qwen3-Reranker-0.6B with Ultrachat, THUIR/T2Ranking and m-a-p/COIG-CQIA for calibration set.
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4.6K
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Parameters
599M
549 MB on disk
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2
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.safetensors538 MB · 97%
Parameter types
How the weights are stored.
I32440M · 73%
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Model card
From the Hugging Face model README
Qwen3-Reranker-0.6B-W4A16-G128
GPTQ Quantized Qwen/Qwen3-Reranker-0.6B with Ultrachat, THUIR/T2Ranking and m-a-p/COIG-CQIA for calibration set.
What's the benefit?
VRAM Usage: 3228M -> 2124M (w/o FA2, according to Embedding model's result).
What's the cost?
I think <5% accuracy, further evaluation on the way...
The Embedding one shows ~0.7%.
How to use it?
pip install compressed-tensors optimum and auto-gptq / gptqmodel, then goto the official usage guide.
- Task
- Text Classification
- Library
- transformers
- Type
- qwen3
- License
- apache-2.0
- Created
- Jun 7, 2025
- Updated
- Jun 7, 2025