Compares embedding vectors for two different texts visually and by numerical metrics. At the present time BERT-Base, Cased (12-layer, 768-hidden, 12-heads, 110M parameters, English language) in DeepPavlov library is used, but it can be extended in the future if needed. Both input and output embeddings from BERT can be compared for two consecutive text inputs. This allows empirical investigation of model characteristics. Vectors are compared by visual silhouette, Euclidean and Cosine distances, and also by difference and side-by-side graphs. github地址： https://github.com/mera-company/nlp-embeddings-visualizer