instructor-embedding
One Embedder, Any Task Instruction-Finetuned Text Embeddings
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
instructor-embedding: ACL 2023 solution for generating instruction-finetuned text embeddings suitable for various NLP applications.
Good fit when
- For tasks requiring contextual understanding through instructions, like interactive systems
- In information retrieval scenarios where relevance and context matter
Avoid when
- When simple keyword matching or non-contextual semantic analysis is sufficient
- If the application requires embeddings trained on very specific domain data not covered by generic instruction-finetuning
Observed Jul 14, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (612d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 20, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install instructor-embeddingSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Provides instruction-finetuned text embeddings for various natural language processing tasks including information retrieval and text evaluation.
Capability facts
- Languages
- python
Source: github.language · Sep 20, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 20, 2026)
conda env create -n instructor python=3.7Source link
Tags
README
Installation It is very easy to use INSTRUCTOR for any text embeddings. You can easily try it out in Colab notebook. In your local machine, we recommend to first create a virtual environment: That will create the environment we used. To use the embedding tool, first install the p...
For agents
This page has a .md twin and JSON over the API.