Spliformer is a self-attention based deep-learning tool that predicts splicing based on pre-mRNA sequences, and visualizes the attention weight score (AWS) of splicing motifs. Spliformer takes a VCF file containing variants of interest as and input and predict the possibility of a variant causing mis-splicing. In addition, it can generate the AWS heatmaps of splicing motifs in the wild type and variant type containing sequences for exploring potential splicing motifs. (The current version of Spliformer is for testing only. The results/papers generated based on Splifomer should cite our paper once it is made available.)