> For the complete documentation index, see [llms.txt](https://docs.texti.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.texti.ai/in-context-learning/hyperparameters.md).

# Hyperparameters

#### Embeddings:

In the context of Large Language Models, embeddings are mathematical representations of words in a high-dimensional space. They capture the semantic relationships between words and serve as a foundation for understanding and generating text. Currently, only "text-embeddings-ada-002" is supported by Texti, but many domain-specific open-source models will soon be available.

#### Similarity Measure:

The similarity measure defines how the model gauges the closeness or similarity between different pieces of text. Currently, Texti only supports "Cosine" as a similarity measure.

#### Chunk Size (Tokens):

This refers to the number of tokens (words or subwords) processed together as a single block or 'chunk' when documents are converted into embeddings.