We cross-matched 1.3 million white dwarf (WD) candidates from Gaia EDR3 with spectral data from LAMOST DR7 within 3′′. Applying machine learning described in our previous work, we spec- troscopically identified 6 190 WD objects after visual inspection, among which 1 496 targets were firstly confirmed. 32 detailed classes were adopted for them, including but not limited to DAB and DB+M. We estimated the atmospheric parameters for the DA and DB type WD using Levenberg- Marquardt least-squares algorithm (LM). Finally, a catalog of WD spectra from LAMOST was provided online.