35 lines
1.0 KiB
Markdown
35 lines
1.0 KiB
Markdown
---
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license: apache-2.0
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base_model: Qwen/Qwen3-1.7B
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tags:
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- quantization
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- reasoning
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- qat
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language:
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- en
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---
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# ReasoningQAT-Qwen3-1.7B-3bit
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This model is a **3-bit pseudo-quantized** version of [Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B), trained with Quantization-Aware Training (QAT) for reasoning tasks.
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## Details
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- **Base model:** Qwen3-1.7B
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- **Quantization:** W3G128 (3-bit weights, group size 128)
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- **Format:** Pseudo-quantized (stored in FP16; weights lie on 3-bit quantization grids)
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- **Method:** ReasoningQAT — QAT combining knowledge distillation with teacher-confidence-weighted DFT loss, trained end-to-end on reasoning data
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## Citation
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```bibtex
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@inproceedings{
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okoshi2026towards,
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title={Towards Quantization-Aware Training for Ultra-Low-Bit Reasoning {LLM}s},
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author={Yasuyuki Okoshi and Hikari Otsuka and Daichi Fujiki and Masato Motomura},
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booktitle={The Fourteenth International Conference on Learning Representations},
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year={2026},
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url={https://openreview.net/forum?id=Azsd2qyK6C}
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}
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```
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