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Found 3 papers, 1 papers with code
Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers
Through extensive experiments on various language models and complexity analysis, we demonstrate that aespa is accurate and efficient in quantizing Transformer models.
Genie: Show Me the Data for Quantization
We also propose a post-training quantization algorithm to enhance the performance of quantized models.
Mr.BiQ: Post-Training Non-Uniform Quantization Based on Minimizing the Reconstruction Error
We thus propose a new post-training non-uniform quantization method, called Mr. BiQ, allowing low bit-width quantization even on Transformer models.
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