Unlocking the Power of Text Embeddings with Databricks GTE Large (English)

The Databricks GTE Large (English) model is a cutting-edge text embedding model designed to enhance your data processing capabilities. Leveraging the prowess of Databricks Foundation Model APIs, this model offers a robust solution for various text-related tasks.

Here are the key features that make Databricks GTE Large a standout:

• Model Type: Text Embeddings
• Language: English
• Model Size: Maps text to a 1024-dimension embedding vector
• Context Length: Supports up to 8192 tokens
• Use Cases: Ideal for retrieval, classification, question-answering, clustering, and semantic search. Perfect for Retrieval Augmented Generation (RAG) with large language models (LLMs).
• Endpoint: Available through the databricks-gte-large-en endpoint
• Performance: Built on the transformer++ encoder backbone (BERT + RoPE + GLU), achieving state-of-the-art scores on benchmarks like MTEB and LoCo.

One of the primary benefits of the Databricks GTE Large model is its ability to find relevant text snippets within large documents. These snippets can then be provided to an LLM to generate more accurate and informative responses, significantly improving the effectiveness of your data-driven applications.

With an input cost of just $0.12999 per 1M tokens and no output cost, this model offers a cost-effective solution for high-performance text embedding tasks.

Unlock the true potential of your data with Databricks GTE Large (English) and take your text processing capabilities to the next level.