sgpt-bloom-7b-underperforms

Summary

A larger embedding model can actually retrieve English documents worse than a smaller one when the bigger model was trained across many languages, because its capacity gets spread thinner across languages instead of focusing on English. This means that for a specific English retrieval task, picking the biggest available model is not automatically the right call; training-data design matters as much as raw parameter count.