Can embeddings be used to represent the meaning of questions and answers?

Aug 3, 2023 ... pgvector adds a new datatype vector, which developers use to store embeddings in regular columns within their database tables. Mar 5, 2024 ... Storage cost scales linearly with dimension, and the choice of embeddings, such as OpenAI's in 1526 dimensions, impacts the overall cost. 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 18, 2021 ... Here, we propose a principled method such that all structural information of a network is parsimoniously encoded. Nov 1, 2023 ... Understanding "text-embedding-ada-002" vector length of 1536 ... No matter how long the input string is, the return of creating embeddings with “ ... Model Choices Voyage currently provides the following text embedding models: Model Context Length (tokens) Embedding Dimension Description voyage-3-large ... 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 ... Jul 22, 2024 ... This paper proposes to learn Scalable Lightweight Embeddings for streaming recommendation, called SCALL, which can adaptively adjust the embedding sizes of ... Here are some test forms on fitting-net size tuning or embedding-net size tuning performed on several different systems. Sep 6, 2023 ... The authors of word2vec are somewhat vague, recommending somewhere between 100 and 1000 dimensions. Other authors pick numbers like 100 or 300.