Papers by Aleksandr Sergeevich Zuev

1 papers
On the Way to Lossless Compression of Language Transformers: Exploring Cross-Domain Properties of Quantization (2024.lrec-main)

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Challenge: Modern Natural Language Processing models have a huge capacity, but this makes it difficult to employ.
Approach: They propose a method to quantize at least 95% of Transformer weights without access to task-specific data so the drop in performance does not exceed 0.02%.
Outcome: The proposed method quantizes 95% of Transformer weights and corresponding activations to INT8 without access to task-specific data so the drop in performance does not exceed 0.02%.

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