The Smallest Doll Is Still a Doll
Open a set of nesting dolls and line them up. The smallest one is tiny, but it is still a whole doll, with a face and a painted dress. Nothing important was left off to make it small.
An from nomic-embed-text is a list of 768 numbers. Every one of them takes 4 bytes to store, for every document you keep. For a million documents that is about 3 GB, just for the embeddings.
So a fair question is: do you need all 768? Could you keep only the first 256, a third of the size, and still find the right documents? Some models lose very little. Others lose more. This lesson measures two of them.
The Words You Need First
Dimension. One number in an . nomic-embed-text gives 768 of them, bge-m3 gives 1,024.
Shorter embedding. Keep only the first N numbers of the list, then scale them so the length is 1 again. Lesson 7 showed why length 1 matters: then cosine, dot product and distance all agree.
dimensions. A setting you can send to Ollama's /api/embed, which does the cutting for you.
Matryoshka. The Russian name for nesting dolls. It is also the name of a way of training an embedding model so that the first numbers carry the most meaning, and the later ones add detail.
Model card. The page a model's makers publish with it, saying what it is for and how to use it. For many models it lives on Hugging Face, a website that hosts models.
Top 5. The right lesson was among the first five results.
Noise. Small differences that happen by chance. They go away, or flip, if you run the test again with other questions.