What are some challenges in evaluating the emotional intelligence of models with different embedding sizes?

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 ... 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 ... Oct 21, 2023 ... We propose the Dynamic Embedding Size Search (DESS) method to minimize the embedding size selection regret on both user and item sides in a non-stationary ... Jun 12, 2024 ... How models can be used to generate vector embeddings. How vector embeddings represent data. In machine learning, the “dimensions” of data do not ... ... 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 ... Nov 9, 2019 ... I'm aware that the num_embeddings argument refers to how many elements we have in our vocabulary, and embedding_dim is simply referring to how ... 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 ... Oct 23, 2023 ... Paper: Towards General Text Embeddings with Multi-stage Contrastive Learning; Embedding Dimension: 768; Model Size: 219 MB. 2. GTE-Large. Model ... Apr 11, 2023 ... My main concern is determining the optimal or maximum sentence size for encoding each embedding. I understand that sentence length plays a crucial role. 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 ...