Instructor Models

**Overview**

The instructor models are embedding models developed by the NLP Group of The University of Hong Kong and packaged using MLflow’s sentence_transformers flavor. The models provided in this listing are

- [instructor_base](https://huggingface.co/hkunlp/instructor-base)
- [instructor_large](https://huggingface.co/hkunlp/instructor-large)
- [instructor_xl](https://huggingface.co/hkunlp/instructor-xl)

Instructor models are licensed under the [Apache License 2.0](https://github.com/xlang-ai/instructor-embedding/blob/main/LICENSE). By installing this listing, you acknowledge and agree to the license.

For example notebooks of using the instructor models in various use cases on Databricks, refer to [the Databricks ML example repository](https://github.com/databricks/databricks-ml-examples/tree/master/llm-models/embedding/instructor).

**Use cases**

The instructor models are embedding models that map text to low-dimensional vectors, and some example use cases are:
- RAG implementation
- Data visualization with clustering
- Semantic search document search engine

**Product details**

The embedding models in this listing can be deployed directly to Databricks Model Serving for immediate use, or loaded for fine-tuning or batch inference use cases. For more details, install the listing and view the provided model cards for each model.

搜集汇总

背景与挑战

背景概述

该数据集包含香港大学NLP组开发的三种嵌入模型（base/large/xl），采用Apache 2.0许可，支持RAG实现、数据聚类和语义搜索等应用场景，可直接部署至Databricks平台使用。