perhaps you’ve already tried this, but does reducing n_neighbours help break apart the large cluster? it also seems that you’re projecting down to 1 dimension with n_components=1, so maybe you get better separate in a higher dimensional space (harder to visualise of course )
another idea could be to combine two UMAP models (docs 13), one to target the large cluster, the other to tackle the remaining clusters.