Field of Study:

Language Model Quantization refers to the process of reducing the precision of the numerical values in a language model to make it smaller and faster. This involves converting the continuous values into discrete counterparts. The main goal of quantization is to reduce the computational and storage requirements of the model, which can be particularly beneficial for deploying NLP models on devices with limited resources. However, it's a challenge to perform quantization without significantly impacting the model's performance.

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