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GPTVQ: The Blessing of Dimensionality for LLM Quantization
In this work we show that the size versus accuracy trade-off of neural network quantization can be significantly improved by increasing the quantization dimensionality.
FP8 versus INT8 for efficient deep learning inference
We theoretically show the difference between the INT and FP formats for neural networks and present a plethora of post-training quantization and quantization-aware-training results to show how this theory translates to practice.
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