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README.md
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---
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base_model:
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- meta-llama/Llama-2-70b-hf
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base_model_relation: quantized
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license: llama2
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---
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# Model Card
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- Base model: `meta-llama/Llama-2-70b-hf`
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- Quantization method: BlockLDLQ with GuidedQuant Hessian
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- Target bit-width: 2
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- Backend kernel: QTIP kernel (HYB variant)
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- Calibration data: RedPajama (1024 sentences / 4096 tokens)
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- Calibration objective: Next-token prediction
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- num_groups (for GuidedQuant Hessian): 2
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# How to run
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- Follow the instruction in https://github.com/snu-mllab/GuidedQuant and https://github.com/Cornell-RelaxML/qtip
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# References
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- [Model Paper](https://arxiv.org/abs/2505.07004)
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