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qdrant-landing/content/course/essentials/day-7/superlinked.md
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@@ -33,10 +33,4 @@ Traditional embedding systems rely on a single model to handle all types of inpu
Each encoder produces its own vector representation that reflects its data domain. These embeddings are then merged into a composite embedding, forming a single, context-rich representation that captures multiple dimensions of meaning. Each encoder produces its own vector representation that reflects its data domain. These embeddings are then merged into a composite embedding, forming a single, context-rich representation that captures multiple dimensions of meaning.
## Resources
- [Superlinked & Qdrant Integration Guide](https://qdrant.tech/documentation/frameworks/superlinked/):
Official Qdrant documentation on integrating Superlinked with Qdrant. Learn how to build advanced vector search applications with multiple encoder types for text, images, numbers, categories, and temporal data.
⭐ **Show your support!** Give Superlinked a star on their GitHub repository: [github.com/superlinked/superlinked](https://github.com/superlinked/superlinked) ⭐ **Show your support!** Give Superlinked a star on their GitHub repository: [github.com/superlinked/superlinked](https://github.com/superlinked/superlinked)