---
title: "Extremely Static Embeddings (ESE)"
description: "Embed text "
image: "https://docs.flowercomputer.com/og/base.png"
---

> Documentation Index
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# Extremely Static Embeddings (ESE)

ESE, our first take on a compiler oriented approach to static embedding. It’s a flattening of a tokenizer and map of embeddings into a perfect hash function. Static embeddings, while less contextually accurate than attention based models, are much faster, and our version is by far the fastest that we know about.

Let's take a look at a simple, complete, example:

```rust
// ese exposes two entry points: encode_single for one string,
// and encode for a batch. both return fixed-size f32 vectors
// whose length is ese::DIMENSIONS (512 by default).

fn main() {
let v = ese::encode_single("hello world");
println!("dims: {}", v.len());
// 512

// batch encode: one embedding per input, same order
let embeddings = ese::encode(["potato", "root vegetable"]);
println!("{} embeddings, each {} dims", embeddings.len(), embeddings[0].len());
// 2 embeddings, each 512 dims
}
```

### Things to know
- Play around with chunk sizes that you feed into ESE, you may find a sweet spot with a smaller size. 
- Be sure to run any rust programs using ESE with `--release` it will make the embedding calls many times faster than running it in debug.
- ESE has a few crate features for changing output dimensions and enabling quantization

Source: https://docs.flowercomputer.com/bogkit/embeddings/index.md