xlang-ai/instructor-embedding
An instruction-finetuned text embedding model that generates task-specific embeddings without requiring task-specific fine-tuning.
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The Instructor model produces text embeddings tailored to any task by providing natural language instructions, enabling classification, retrieval, clustering, and semantic similarity without model fine-tuning. It achieves state-of-the-art results across 70 diverse embedding benchmarks in science, finance, and other domains. The repository provides pre-trained checkpoints, Python utilities for encoding text, and supports use cases including custom embedding generation, similarity computation, and information retrieval pipelines.
Frequently asked
- What is xlang-ai/instructor-embedding?
- An instruction-finetuned text embedding model that generates task-specific embeddings without requiring task-specific fine-tuning.
- Is instructor-embedding open source?
- Yes — xlang-ai/instructor-embedding is open source, released under the Apache-2.0 license.
- What language is instructor-embedding written in?
- xlang-ai/instructor-embedding is primarily written in Python.
- How popular is instructor-embedding?
- xlang-ai/instructor-embedding has 2k stars on GitHub.
- Where can I find instructor-embedding?
- xlang-ai/instructor-embedding is on GitHub at https://github.com/xlang-ai/instructor-embedding.