What are some architectures that are particularly well-suited for processing long sequences with high-dimensional embeddings?

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 ... titan-embed-text-v2:0 ) can intake up to 8,192 tokens or 50,000 characters and outputs a vector of 1,024 dimensions. The model is optimized for text retrieval ... ... Scale Semantic Embedding. PLoS Comput Biol 7(1): e1001047. doi:10.1371/journal.pcbi.1001047. Editor: Michael Levitt, Stanford University, United States of ... Sep 24, 2021 ... As for the format, in the format section of each page you have a setting called "Page Size" where you can set a specific page size type, 16:9, 4 ... In this paper, we suggest a simple method for estimating τ ∗ and τ w based on symbolic analysis and symbolic entropy. They feature lower costs, higher multilingual performance, and new parameters to control the overall size. What are embeddings? OpenAI's text embeddings measure ... Sep 21, 2024 ... What do you mean exactly with "embedding length" ? If I run "ollama run llama3.1" and then type "/show info" it says that "embedding length" is 4096. Apr 8, 2024 ... What are embedding models? Embedding models are models that are trained specifically to generate vector embeddings ... Parameter Size. mxbai-embed ... Jan 28, 2020 ... Let's talk about Spatial Embedding. Consider a Basket Ball: and be yourself my friendly Amoeba Scientist Amoeba Joe: You live your full life ... The Granite Embedding lineup includes four different models of varying sizes: granite-embedding-30m-english: English only model that produces embedding vectors ...