Update index.mdx

Author: Michellehbn

docs/source/index.mdx

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 # Inference Endpoints
 
-Inference Endpoints offers a secure production solution to easily deploy any model from the Hub on dedicated and autoscaling infrastructure managed by Hugging Face. 
+Inference Endpoints offers a secure production solution to easily deploy any model from the Hub on dedicated and autoscaling infrastructure managed by Hugging Face.
 
 A Hugging Face Endpoint is built from a [Hugging Face Model Repository](https://huggingface.co/models). When an Endpoint is created, the service creates image artifacts that are either built from the model you select or a custom-provided container image. The image artifacts are completely decoupled from the Hugging Face Hub source repositories to ensure the highest security and reliability levels.
 
 Inference Endpoints support all of the [Transformers, Sentence-Transformers and Diffusers tasks](/docs/inference-endpoints/supported_tasks) as well as [custom tasks](/docs/inference-endpoints/guides/custom_handler) not supported by Transformers yet.
 
 In addition, Inference Endpoints gives you the option to use a custom container image managed on an external service, for instance, [Docker Hub](https://hub.docker.com/), [AWS ECR](https://aws.amazon.com/ecr/?nc1=h_ls), [Azure ACR](https://azure.microsoft.com/en-gb/products/container-registry/), or [Google GCR](https://cloud.google.com/artifact-registry/docs?h%3A=en). 
 
-Inference Endpoints support all container types, for example: vLLM (virtual large language model), TGI (text-generation-inference), TEI (text-embeddings-inference), llama.cpp, and more.
+Inference Endpoints support all container types, for example: vLLM, TGI (text-generation-inference), TEI (text-embeddings-inference), llama.cpp, and more.
 
 ![creation-flow](https://raw.githubusercontent.com/huggingface/hf-endpoints-documentation/main/assets/creation_flow.png)