New Function
Instructor Embeddings
Instruction-tuned embeddings for precise task control.
Fine-grained control via instructionsHigh performance on specific tasksAdaptable to diverse classification needOpen-source library
Today's score
87.0
Where it ranks today
Best for / Not great for
Best for
- Task-specific embeddings (e.g., classification, retrieval)
- Zero-shot or few-shot learning scenarios
- Controlling embedding dimensions precisely
- Building custom classification systems
Not great for
- General-purpose semantic search without instruction tuning
- Users unfamiliar with instruction prompting
- Extremely high-volume, low-cost scenarios requiring standard models
Why it ranks here
Instructor embeddings offer a unique approach by allowing users to guide embedding generation with natural language instructions. This fine-tuning capability makes them particularly strong for classification tasks and scenarios requiring highly specific embedding outputs, differentiating them from more general-purpose models.
30-day trend
Score breakdown
Search trends85
Benchmarks86
Developer buzz92
News mentions85
Pricing
API: $0.00 in · $0.00 out per 1M tokens · Consumer: $0.00/mo
Pricing plans
Popular
Free (Self-hosted)
Open-source library for instruction-based embeddings
Free
- Python library
- Instruction-based fine-tuning
- Supports various underlying models
- Full control