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How to efficiently serve ever-larger trained natural language models in practice has become exceptionally challenging even for powerful cloud servers due to their prohibitive memory/computation requirements.
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Zhen Dong, Zhewei Yao, Amir Gholami, Michael W Mahoney, and Kurt Keutzer · 2019
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Steven K Esser, Jeffrey L McKinstry, Deepika Bablani, Rathinakumar Appuswamy, and Dharmendra S Modha · 2019
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Angela Fan, Edouard Grave, and Armand Joulin · 2019
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GPT-NeoX: Large scale autoregressive language modeling in pytorch, 2021
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A survey of quantization methods for efficient neural network inference
Amir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael W Mahoney, and Kurt Keutzer · 2021
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I-bert: Integer-only bert quantization
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Post-training quantization for vision transformer
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