BGE v1.5 Models

**Overview**

The bge_v1_5 models are embedding models developed by Beijing Academy of Artificial Intelligence and packaged using MLflow’s sentence_transformers flavor. The models provided in this listing are

- [bge_large_en_v1_5](https://huggingface.co/BAAI/bge-large-en-v1.5)
- [bge_base_en_v1_5](https://huggingface.co/BAAI/bge-base-en-v1.5)
- [bge_small_en_v1_5](https://huggingface.co/BAAI/bge-small-en-v1.5)

Bge_v1_5 models are licensed under the [MIT License](https://github.com/FlagOpen/FlagEmbedding/blob/master/LICENSE). By installing this listing, you acknowledge and agree to the license.

For example notebooks of using the bge_v1_5 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/bge).

**Use cases**

The bge_v1_5 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

BGE v1.5模型是由北京智源人工智能研究院开发的文本嵌入模型，包含bge_large_en_v1_5、bge_base_en_v1_5和bge_small_en_v1_5三个版本，适用于RAG实现、语义搜索和聚类可视化等任务，并支持直接部署或微调使用。