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Text Embedding Ada 002
Classic OpenAI embeddings
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See available modelsAbout the model
Text Embedding Ada 002 is the classic OpenAI embeddings model, time-tested and widely used across the industry. It turns text into vectors for semantic search and RAG. It is supported by many libraries, vector databases and ready-made pipelines, which makes integration easier. The resulting representations are suitable for clustering, recommendations, deduplication and classification. The model works with many languages, including Russian. It is chosen for compatibility, especially when migrating existing projects.
Strengths
- Time-tested solution
- Broad compatibility with tools
- Supported by vector databases and libraries
- Vectors for clustering and recommendations
- Suitable for RAG and semantic search
- Works with many languages, including Russian
Where to use it
- Semantic search across documents
- RAG pipelines and question-answering systems
- Clustering and topic grouping
- Recommendation systems
- Deduplication and similarity search
- Text classification based on vectors