doc: clarify the use case

meakbiyik · Sep 25, 2023 · bd9a25d · bd9a25d
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diff --git a/README.md b/README.md
@@ -4,6 +4,8 @@
 
 Effortlessly cache PyTorch module outputs on-the-fly with `torchcache`.
 
+Particularly useful for caching and serving the outputs of computationally expensive large, pre-trained PyTorch modules, such as vision transformers. Note that gradients will not flow through the cached outputs.
+
 - [Features](#features)
 - [Installation](#installation)
 - [Basic usage](#basic-usage)

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -5,6 +5,8 @@ Welcome to torchcache!
 
 `torchcache` offers an effortless way to cache PyTorch module outputs on-the-fly. By caching the outputs of a module, you can save time and resources when running the same pre-trained model on the same inputs multiple times.
 
+Note that gradients will not flow through the cached outputs.
+
 .. toctree::
    :maxdepth: 2
    :caption: Table of Contents: