GTE Models

**Note:**
Usage of this model family from Marketplace is no longer recommended. Customers that want to use GTE models should use the installed GTE models found in **system.ai** in their metastores.

**Overview**

The gte models are embedding models developed by Alibaba DAMO Academy and packaged using MLflow’s sentence_transformers flavor. The models provided in this listing are

- [gte_base](https://huggingface.co/thenlper/gte-base)
- [gte_large](https://huggingface.co/thenlper/gte-large)
- [gte_small](https://huggingface.co/thenlper/gte-small)

Gte models are licensed under the [MIT License](https://choosealicense.com/licenses/mit/). By installing this listing, you acknowledge and agree to the license.

For example notebooks of using the gte 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/gte).

**Use cases**

The gte 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.