@ -75,3 +75,15 @@ An image embedding operator takes an image as input. it extracts the embedding a
The extracted facial landmarks.
# More Resources
- [Approximate Nearest Neighbors Oh Yeah (Annoy) - Zilliz blog](https://zilliz.com/learn/approximate-nearest-neighbor-oh-yeah-ANNOY): Discover the capabilities of Annoy, an innovative algorithm revolutionizing approximate nearest neighbor searches for enhanced efficiency and precision.
- [How to Get the Right Vector Embeddings - Zilliz blog](https://zilliz.com/blog/how-to-get-the-right-vector-embeddings): A comprehensive introduction to vector embeddings and how to generate them with popular open-source models.
- [Hugging Face Inference Endpoints & Zilliz Cloud](https://zilliz.com/product/integrations/hugging-face): nan
- [Transforming Text: The Rise of Sentence Transformers in NLP - Zilliz blog](https://zilliz.com/learn/transforming-text-the-rise-of-sentence-transformers-in-nlp): Everything you need to know about the Transformers model, exploring its architecture, implementation, and limitations
- [Understanding ImageNet: A Key Resource for Computer Vision and AI Research](https://zilliz.com/glossary/imagenet): The large-scale image database with over 14 million annotated images. Learn how this dataset supports advancements in computer vision.
- [Build a Multimodal Search System with Milvus - Zilliz blog](https://zilliz.com/blog/how-vector-dbs-are-revolutionizing-unstructured-data-search-ai-applications): Implementing a Multimodal Similarity Search System Using Milvus, Radient, ImageBind, and Meta-Chameleon-7b
- [Zilliz-Hugging Face partnership - Explore transformer data model repo](https://zilliz.com/partners/hugging-face): Use Hugging Faceâs community-driven repository of data models to convert unstructured data into embeddings to store in Zilliz Cloud, and access a code tutorial.
