Stellar chemistry contains information on the environment in which the star was born. Therefore, measuring the chemical abundances of stars in the Milky Way, such as the overall metallicity [M/H] and the alpha-abundance [alpha/M], is essential in Galactic astronomy. We estimate ([M/H], [alpha/M]) for giants and dwarfs in low dust extinction region from the Gaia DR3 XP spectra by using tree-based machine-learning models trained on APOGEE DR17 (Abdurro’uf et al. 2022) and the metal-poor star sample of Li et al. (2022). Here, we upload the catalogues of ([M/H], [alpha/M]) for 182 million stars. The data are divided into 10 fits files. The i-th file (i=1,2,...,10) contains stars with E(B-V) value between 0.1*(i-1) and 0.1*i. Because our machine-learning models are trained on stars with low dust extinction (E(B-V)<0.1), we recommend using 48 million stars with low-dust extinction region with 0