Class Embedder

Namespace

LMKit.Embeddings

Assembly

LM-Kit.NET.dll

A class designed for generating embeddings. It facilitates execution of tasks related to natural language and coding, such as semantic search, clustering, topic modeling, and classification.

public sealed class Embedder

Inheritance

object

Embedder

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

Embedder(LLM)

Initializes a new instance of the Embedder class.

Properties

Model

Gets the LLM instance associated with this object.

Methods

GetCosineSimilarity(IList<float>, IList<float>)

Calculates the cosine similarity between two embedding vectors, representing the cosine of the angle between them in a multidimensional space.

GetEmbeddings(IEnumerable<IList<int>>, CancellationToken)

Generates embedding vectors for a collection of tokenized texts. Each vector represents a text in a high-dimensional space, enabling various natural language processing tasks by capturing semantic meaning.

GetEmbeddings(IEnumerable<string>, CancellationToken)

Generates embedding vectors for a collection of text strings. Each vector represents a text in a high-dimensional space, enabling various natural language processing tasks by capturing semantic meaning.

GetEmbeddings(IList<int>, CancellationToken)

Generates the embedding vector for a given tokenized text. This vector represents the text in a high-dimensional space, enabling various natural language processing tasks by capturing semantic meaning.

GetEmbeddings(string, CancellationToken)

Generates the embedding vector for a given text string. This vector represents the text in a high-dimensional space, enabling various natural language processing tasks by capturing semantic meaning.

GetEmbeddingsAsync(IEnumerable<IList<int>>, CancellationToken)

Asynchronously generates embedding vectors for a collection of tokenized texts. Each vector represents a text in a high-dimensional space, enabling various natural language processing tasks by capturing semantic meaning.

GetEmbeddingsAsync(IEnumerable<string>, CancellationToken)

Asynchronously generates embedding vectors for a collection of text strings. Each vector represents a text in a high-dimensional space, enabling various natural language processing tasks by capturing semantic meaning.

GetEmbeddingsAsync(IList<int>, CancellationToken)

Asynchronously generates the embedding vector for a given tokenized text. This vector represents the text in a high-dimensional space, enabling various natural language processing tasks by capturing semantic meaning.

GetEmbeddingsAsync(string, CancellationToken)

Asynchronously generates the embedding vector for a given text string. This vector represents the text in a high-dimensional space, enabling various natural language processing tasks by capturing semantic meaning.