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- using LLama.Common;
-
- namespace LLama.Examples.Examples
- {
- public class GetEmbeddings
- {
- public static void Run()
- {
- string modelPath = UserSettings.GetModelPath();
-
- Console.ForegroundColor = ConsoleColor.DarkGray;
- var @params = new ModelParams(modelPath) { EmbeddingMode = true };
- using var weights = LLamaWeights.LoadFromFile(@params);
- var embedder = new LLamaEmbedder(weights, @params);
-
- Console.ForegroundColor = ConsoleColor.Yellow;
- Console.WriteLine(
- """
- This example displays embeddings from a text prompt.
- Embeddings are numerical codes that represent information like words, images, or concepts.
- These codes capture important relationships between those objects,
- like how similar words are in meaning or how close images are visually.
- This allows machine learning models to efficiently understand and process complex data.
- Embeddings of a text in LLM is sometimes useful, for example, to train other MLP models.
- """); // NOTE: this description was AI generated
-
- while (true)
- {
- Console.ForegroundColor = ConsoleColor.White;
- Console.Write("Please input your text: ");
- Console.ForegroundColor = ConsoleColor.Green;
- var text = Console.ReadLine();
- Console.ForegroundColor = ConsoleColor.White;
-
- float[] embeddings = embedder.GetEmbeddings(text).Result;
- Console.WriteLine($"Embeddings contain {embeddings.Length:N0} floating point values:");
- Console.ForegroundColor = ConsoleColor.DarkGray;
- Console.WriteLine(string.Join(", ", embeddings.Take(20)) + ", ...");
- Console.WriteLine();
- }
- }
- }
- }
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