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Model Selection
Choosing the right embedding model matters for semantic search performance. Different models excel in different scenarios, and the choice affects speed, quality, and resource requirements.
Leaderboards
Hugging Face hosts an embedding model leaderboard that compares models across many retrieval and classification tasks.
At the time of writing, Cohere and Mixedbread models are strong default options.
General Purpose Models
- Use case: Broad semantic understanding across domains
- Examples:
all-MiniLM-L6-v2,all-mpnet-base-v2 - Best for: Movie search, general document retrieval
Domain-Specific Models
- Use case: Specialized knowledge (medical, legal, scientific)
- Examples:
allenai-specter,microsoft/BiomedNLP-PubMedBERT - Best for: Technical documentation, research papers
Multilingual Models
- Use case: Data in multiple languages in the same search system
- Examples:
paraphrase-multilingual-MiniLM-L12-v2 - Best for: International movie databases