I am comparing words in HuggingFace web UI using
e5-small-v2, one of the best vector embedding models:
Assuming that the scores are in the range from 0 to 1, how come all the scores are so high? In fact, I was not able to produce any example with a score below 0.7. Is there something basic I am missing about vector embeddings?