Are there any theoretical frameworks for determining the optimal embedding size?

Currently, many state-of-the-art models produce embeddings with 1024 dimensions, each of which is encoded in float32 , i.e., they require 4 bytes per dimension. Jul 14, 2020 ... The models we trained use for instance token embeddings of size 500 and feature embeddings of 12 to get to 512 in total. That makes sense ... Feb 20, 2024 ... Vectors are very long and complex. For instance, OpenAI's vector size is typically 1536, which means each embedding is an array of 1536 floating ... 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 ... For other users embedding many documents, this batch size may be too small. # set the batch size to 42 embed_model = OpenAIEmbedding(embed_batch_size=42) ... Dec 9, 2023 ... ... size or length. Common vector dimensionalities include 384 ... A single dimension in a vector embedding does not mean anything, as ... Apr 8, 2023 ... The output dimension is mantained, since values coming from each attention head are concatenated and then projected with a matrix WO∈Rhdv×dmodel ... Response. OK. idstring. embeddingsobject. An object with different embedding types. The length of each embedding type array will be the same as the length of ... Jul 8, 2023 ... The 'dimension' of an embedding refers to the length of the vector representing an object. So, an embedding with 1536 dimensions means that ... Your prospect receives the image as an attachment with its original size and shape. This method is ideal when the file needs to be preserved. Embeds. An image ...