What is the role of embedding size in anomaly detection?

An embedding refers to the reduction of high-dimensional data, such as unstructured text, to a representation with fewer dimensions, such as a vector. Mar 7, 2025 ... We've improved our context length from previous models allowing you to embed large chunks of text, code, or other data. Output dimensions of 3K ... Jun 4, 2024 ... Embedding dimensions: This is the length of the embedding vector. ... For common RAG applications, a good chunk size for an embedding is typically ... My response was solely for the cloud version. Here's a small clarification : I mistook your mention of maximum size for Office Powerpoint Macro , as the file ... Jan 12, 2021 ... In this paper, we proposed a novel approach, named PEP (short for Plug-in Embedding Pruning), to reduce the size of the embedding table while avoiding the drop ... Model size: the size of a model indicates how easy it will be to run. All ... embeddings # openai embedding function def embed(docs: list[str]) -> list ... Jan 25, 2024 ... ... embedding model and creates embeddings with up to 3072 dimensions. ... embedding-ada-002 embedding with a size of 1536. ada v2, text ... ... embed configuration. Here I could define the size as I like. In the new storymaps I don't have a place to do that. They even change the embedded code to ... May 7, 2021 ... We present network embedding algorithms that capture information about a node from the local distribution over node attributes around it. In data science, the term dimension typically refers to a feature or attribute of the data. Higher-dimensional data in AI refers to datasets with many features ...