Struct HashEmbedder 

pub struct HashEmbedder { /* private fields */ }

FNV-1a feature hashing embedder.

Projects text into a fixed-dimension vector using FNV-1a hashing. Each token contributes to one dimension, with the hash determining both which dimension and the sign (+1/-1) of the contribution.

Implementations

impl HashEmbedder

pub fn new(dimension: usize) -> Self

Create a new hash embedder with the specified dimension.

Arguments

• dimension - The output vector dimension. Common values: 256, 384, 512. Higher dimensions reduce hash collisions but increase storage.

Panics

Panics if dimension is 0.

pub fn default_dimension() -> Self

Create a new hash embedder with the default dimension (384).

Trait Implementations

impl Clone for HashEmbedder

fn clone(&self) -> HashEmbedder

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for HashEmbedder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for HashEmbedder

fn default() -> Self

Returns the “default value” for a type.

impl SyncEmbed for HashEmbedder

fn embed_sync(&self, text: &str) -> EmbedderResult<Vec<f32>>

Synchronously embed a single text into a vector.

fn embed_batch_sync(&self, texts: &[&str]) -> EmbedderResult<Vec<Vec<f32>>>

Synchronously embed a batch of texts.

fn dimension(&self) -> usize

The output dimensionality of embedding vectors.

fn id(&self) -> &str

Unique, stable identifier for this embedder (stored in index headers).

fn is_semantic(&self) -> bool

Whether this embedder produces semantically meaningful vectors.

fn category(&self) -> ModelCategory

The speed/quality category of this embedder.

fn tier(&self) -> ModelTier

Default progressive tier assignment.

fn model_name(&self) -> &str

Human-readable model name.

fn is_ready(&self) -> bool

Whether the embedder is loaded and operational.

fn supports_mrl(&self) -> bool

Whether this model supports Matryoshka Representation Learning.