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Showing 1 to 2 of 2 for “"Post-Training Quantization (PTQ)"”.

  1. Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization

    We consider the problem of accurate quantization for language models, where both the weights and activations are quantized to 4 bits per parameter with uniform quantization, the lowest bitwidth format natively supported by existing GPU hardware. In this context, the key challenge is activation …

    mit Repository record for Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization (opens in a new tab)

  2. Resource-efficient optimizations of 3D vision models for segmentation and detection

    Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01

    uiuc Repository record for Resource-efficient optimizations of 3D vision models for segmentation and detection (opens in a new tab)