From 408a9348fa0c2e0f39fb01ca192e851ef0540a07 Mon Sep 17 00:00:00 2001 From: Benoit Chevallier-Mames Date: Tue, 9 Apr 2024 16:12:00 +0200 Subject: [PATCH] polish --- fhe-endpoints.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/fhe-endpoints.md b/fhe-endpoints.md index e4b0a3c82a8..8f845b9bc94 100644 --- a/fhe-endpoints.md +++ b/fhe-endpoints.md @@ -13,7 +13,7 @@ Eighteen months ago, Zama started [Concrete ML](https://github.com/zama-ai/concr From the start, we wanted to pre-compile some FHE-friendly networks and make them available somewhere on the internet, allowing users to use them trivially. We are ready today! And not in a random place on the internet, but directly on Hugging Face. -More precisely, we use Hugging Face [Endpoints](https://huggingface.co/docs/inference-endpoints/en/index) and [custom inference handlers](https://huggingface.co/docs/inference-endpoints/en/guides/custom_handler), to be able to store our Concrete ML models and let users deploy on HF machines in one click. At the end of this blog post, you will understand how to use pre-compiled models and how to prepare your pre-compiled models. This blog can also be considered as another tutorial for custom inference handlers. +More precisely, we use Hugging Face [Endpoints](https://huggingface.co/docs/inference-endpoints/en/index) and [custom inference handlers](https://huggingface.co/docs/inference-endpoints/en/guides/custom_handler), to be able to store our Concrete ML models and let users deploy on HF machines in one click. At the end of this blog post, you will understand how to use pre-compiled models and how to prepare yours. This blog can also be considered as another tutorial for custom inference handlers. ## Deploying a pre-compiled model