Deploy Embedding Models with Hugging Face Inference Endpoints

The rise of Generative AI and LLMs like ChatGPT has increased the interest and importance of embedding models for a variety of tasks especially for retrievel augemented generation, like search or chat with your data. Embeddings are helpful since they represent sentences, images, words, etc. as numeric vector representations, which allows us to map semantically related items and retrieve helpful information. This helps us to provide relevant context for our prompt to improve the quality and specificity of generation.

Compared to LLMs are Embedding Models smaller in size and faster for inference. That is very important since you need to recreate your embeddings after you changed your model or improved your model fine-tuning. Additionally, is it important that the whole retrieval augmentation process is as fast as possible to provide a good user experience.

In this blog post, we will show you how to deploy open-source Embedding Models to Hugging Face Inference Endpoints using Text Embedding Inference, our managed SaaS solution that makes it easy to deploy models. Additionally, we will teach you how to run large scale batch requests.

1. What is Hugging Face Inference Endpoints
2. What is Text Embedding Inference
3. Deploy Embedding Model as Inference Endpoint
4. Send request to endpoint and create embeddings

Before we start, let's refresh our knowledge about Inference Endpoints.

1. What is Hugging Face Inference Endpoints?

Hugging Face Inference Endpoints offers an easy and secure way to deploy Machine Learning models for use in production. Inference Endpoints empower developers and data scientists to create Generative AI applications without managing infrastructure: simplifying the deployment process to a few clicks, including handling large volumes of requests with autoscaling, reducing infrastructure costs with scale-to-zero, and offering advanced security.

Here are some of the most important features:

You can get started with Inference Endpoints at: https://ui.endpoints.huggingface.co/