INSTRUCTOR Embeddings
Definition
INSTRUCTOR embeddings take a task instruction into account when representing texts.
INSTRUCTOR embeddings are numerical text representations generated together with a task or domain instruction. This instruction describes what the representation is used for, for example, for a search.
Simply explained
Like a sorting order to an archive: The same text is classified under a specific search task. However, the numbers are not human-readable index cards.
Why it matters in practice
For deployment, a comparison of suitable instructions based on typical search queries is recommended.
Example from business
Possible example: A search prototype represents queries and documents with explicitly described tasks in the same procedure.
Limits and pitfalls
- The instruction is part of the input and should not change unnoticed. The research results do not replace a test with your own documents.
Origin & history
The cited 2023 version describes instruction-based fine-tuned text representations for different tasks.
Use in mid-sized companies
- Possible application areas are internal document search and text classification; task instructions would be compared based on professionally evaluated results.
Frequently asked questions
Are these finished answers?
No, these are representations of texts for downstream processing.
Must it be retrained for each new task?
The work describes adaptation via instructions without additional task-specific training.
Sources
- One Embedder, Any Task: Instruction-Finetuned Text Embeddings · Su et al. (2023): One Embedder, Any Task: Instruction-Finetuned Text Embeddings
Editorially reviewed on: