Quanto: a pytorch quantization toolkit

Quantization is a technique to reduce the computational and memory costs of evaluating Deep Learning Models by representing their weights and activations with low-precision data types like 8-bit integer (int8) instead of the usual 32-bit floating point (float32). Reducing the number of bits means the resulting model requires less memory storage, which is crucial for deploying Large Language Models

[misshiki]

“いくつかのユニークな機能を提供する多用途の pytorch 量子化ツールキットであるquantoを紹介”

[deejayroka]

“Quantization is a technique to reduce the computational and memory costs of evaluating Deep Learning Models by representing their weights and activations with low-precision data types like 8-bit integer (int8) instead of the usual 32-bit floating point (float32).”