@ -95,3 +95,12 @@ It returns a text emabedding in numpy.ndarray.
Get a list of supported model names.
# More Resources
- [All-Mpnet-Base-V2: Enhancing Sentence Embedding with AI - Zilliz blog](https://zilliz.com/learn/all-mpnet-base-v2-enhancing-sentence-embedding-with-ai): Delve into one of the deep learning models that has played a significant role in the development of sentence embedding: MPNet.
- [The guide to text-embedding-ada-002 model | OpenAI](https://zilliz.com/ai-models/text-embedding-ada-002): text-embedding-ada-002: OpenAI's legacy text embedding model; average price/performance compared to text-embedding-3-large and text-embedding-3-small.
- [OpenAI text-embedding-3-large | Zilliz](https://zilliz.com/ai-models/text-embedding-3-large): Building GenAI applications with text-embedding-3-large model and Zilliz Cloud / Milvus
- [Mastering Text Similarity Search with Vectors in Zilliz Cloud - Zilliz blog](https://zilliz.com/learn/mastering-text-similarity-search-with-vectors-in-zilliz-cloud): We explore the fundamentals of vector embeddings and demonstrated their application in a practical book title search using Zilliz Cloud and OpenAI embedding models.
- [A Guide to Using OpenAI Text Embedding Models for NLP Tasks - Zilliz blog](https://zilliz.com/learn/guide-to-using-openai-text-embedding-models): A comprehensive guide to using OpenAI text embedding models for embedding creation and semantic search.
