Crate fastembed

FastEmbed - Fast, light, accurate library built for retrieval embedding generation.

The library provides the TextEmbedding struct to interface with text embedding models.

Instantiating TextEmbedding

use fastembed::{TextEmbedding, InitOptions, EmbeddingModel};

// With default InitOptions
let model = TextEmbedding::try_new(Default::default())?;

// List all supported models
dbg!(TextEmbedding::list_supported_models());

// With custom InitOptions
let model = TextEmbedding::try_new(InitOptions {
    model_name: EmbeddingModel::BGEBaseENV15,
    show_download_progress: false,
    ..Default::default()
})?;

Find more info about the available options in the InitOptions documentation.

Embeddings generation

 let documents = vec![
    "passage: Hello, World!",
    "query: Hello, World!",
    "passage: This is an example passage.",
    // You can leave out the prefix but it's recommended
    "fastembed-rs is licensed under MIT"
    ];

 // Generate embeddings with the default batch size, 256
 let embeddings = model.embed(documents, None)?;

 println!("Embeddings length: {}", embeddings.len()); // -> Embeddings length: 4

Structs

• InitOptions
  Options for initializing the TextEmbedding model
• InitOptionsUserDefined
  Options for initializing UserDefinedEmbeddingModel
• ModelInfo
  Data struct about the available models
• TextEmbedding
  Rust representation of the TextEmbedding model
• TokenizerFiles
• UserDefinedEmbeddingModel
  Struct for “bring your own” embedding models

Enums

• EmbeddingModel
• ExecutionProviderDispatch
  Execution provider container. See the ONNX Runtime docs for more info on execution providers. Execution providers are actually registered via the functions crate::SessionBuilder (per-session) or EnvironmentBuilder (default for all sessions in an environment).

Functions

• read_file_to_bytes
  Read a file to bytes.

Type Aliases

• Embedding
  Type alias for the embedding vector