Verified75% confidenceFactTime unknown
PTQ (Post-Training Quantization) does not require retraining the model; quantization can be completed with only a small amount of calibration data, typically a few hundred to a few thousand calibration samples.
3
Sources
75%
Confidence
Long-term
Relevance
6/1/2026
First Seen
Sources
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Related Claims
UnverifiedOn small datasets, DETR weights pre-trained on large-scale datasets such as COCO should be used for fine-tuning rather than training from scratch72% similarUnverifiedViTs usually require larger-scale data for pretraining, otherwise they tend to underfit on small datasets.69% similarUnverifiedThe original DETR requires 500 epochs of training on the COCO dataset (approximately 118,000 training images) to achieve satisfactory performance.67% similarUnverifiedBoth GPTQ and AWQ belong to Post-Training Quantization, requiring no retraining of the model and only a small amount of calibration data.67% similar
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