The World Health Organization reported the covid-19 virus a global pandemic on March 11, 2020. The RT-PCR test, also known as reverse polymerase chain reaction is used to determine the ailment. It does, however, suffer from false negative. Due to its potential to rapidly mutate, early discovery of the disease is essential for combating its further spread. Medical imaging approaches including Computed Tomography (CT), chest X-rays and computer vision techniques are used to assess covid-19. A vision transformer (VIT) based model for covid-19 detection in chest X-ray images is proposed. Contrast Limited Adaptive Histogram Equalization (CLAHE) and Gaussian Filter is used in the preprocessing step to improve the contrast of the chest X-rays images. The study compares the proposed technique to pre-trained convolutional neural network (CNN) models.