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Found 4 papers, 1 papers with code
Towards Accurate Post-training Quantization for Reparameterized Models
Our framework outperforms previous methods by approximately 1\% for 8-bit PTQ and 2\% for 6-bit PTQ, showcasing its superior performance.
Dual Grained Quantization: Efficient Fine-Grained Quantization for LLM
Fine-grained quantization has smaller quantization loss, consequently achieving superior performance.
BiViT: Extremely Compressed Binary Vision Transformers
To solve this, we propose Softmax-aware Binarization, which dynamically adapts to the data distribution and reduces the error caused by binarization.
BiViT: Extremely Compressed Binary Vision Transformer
To solve this, we propose Softmax-aware Binarization, which dynamically adapts to the data distribution and reduces the error caused by binarization.
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