From c2cb32a8120933c80ee89f9363e617f3f0edc8d6 Mon Sep 17 00:00:00 2001
From: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Date: Mon, 8 Aug 2022 08:53:52 -0700
Subject: [PATCH] =?UTF-8?q?=20=E2=9C=A8=20update=20to=20use=20interlibrary?=
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---
 docs/source/en/accelerate.mdx | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/source/en/accelerate.mdx b/docs/source/en/accelerate.mdx
index dad9b4b8ea802d..7a16c59bdee729 100644
--- a/docs/source/en/accelerate.mdx
+++ b/docs/source/en/accelerate.mdx
@@ -22,7 +22,7 @@ Get started by installing 🤗 Accelerate:
 pip install accelerate
 ```
 
-Then import and create an [`Accelerator`](https://huggingface.co/docs/accelerate/package_reference/accelerator#accelerate.Accelerator) object. `Accelerator` will automatically detect your type of distributed setup and initialize all the necessary components for training. You don't need to explicitly place your model on a device.
+Then import and create an [`~accelerate.Accelerator`] object. The [`~accelerate.Accelerator`] will automatically detect your type of distributed setup and initialize all the necessary components for training. You don't need to explicitly place your model on a device.
 
 ```py
 >>> from accelerate import Accelerator
@@ -32,7 +32,7 @@ Then import and create an [`Accelerator`](https://huggingface.co/docs/accelerate
 
 ## Prepare to accelerate
 
-The next step is to pass all the relevant training objects to the [`prepare`](https://huggingface.co/docs/accelerate/package_reference/accelerator#accelerate.Accelerator.prepare) method. This includes your training and evaluation DataLoaders, a model and an optimizer:
+The next step is to pass all the relevant training objects to the [`~accelerate.Accelerator.prepare`] method. This includes your training and evaluation DataLoaders, a model and an optimizer:
 
 ```py
 >>> train_dataloader, eval_dataloader, model, optimizer = accelerator.prepare(
@@ -42,7 +42,7 @@ The next step is to pass all the relevant training objects to the [`prepare`](ht
 
 ## Backward
 
-The last addition is to replace the typical `loss.backward()` in your training loop with 🤗 Accelerate's [`backward`](https://huggingface.co/docs/accelerate/package_reference/accelerator#accelerate.Accelerator.backward) method:
+The last addition is to replace the typical `loss.backward()` in your training loop with 🤗 Accelerate's [`~accelerate.Accelerator.backward`]method:
 
 ```py
 >>> for epoch in range(num_epochs):