This is an automated email from the ASF dual-hosted git repository.
orpiske pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/camel.git
commit 4a997b40cfbd634621668e6f185f401098787ac5
Author: Otavio Rodolfo Piske <angusyo...@gmail.com>
AuthorDate: Mon Feb 19 13:07:02 2024 +0100
CAMEL-20410: documentation fixes for camel-djl
- Fixed samples
- Fixed grammar and typos
- Fixed punctuation
- Added and/or fixed links
---
components/camel-djl/src/main/docs/djl-component.adoc | 13 +++++--------
1 file changed, 5 insertions(+), 8 deletions(-)
diff --git a/components/camel-djl/src/main/docs/djl-component.adoc
b/components/camel-djl/src/main/docs/djl-component.adoc
index 380780bee66..d00fbbaaaac 100644
--- a/components/camel-djl/src/main/docs/djl-component.adoc
+++ b/components/camel-djl/src/main/docs/djl-component.adoc
@@ -14,13 +14,10 @@
*{component-header}*
-The *Deep Java Library* component is used to infer Deep Learning models from
message exchanges data.
-This component uses https://djl.ai/[Deep Java Library] as underlying library.
+The *Deep Java Library* component is used to infer deep learning models from
message exchanges data.
+This component uses the https://djl.ai/[Deep Java Library] as the underlying
library.
-In order to use the DJL component, Maven users will need to add the
-following dependency to their `pom.xml`:
-
-*pom.xml*
+To use the DJL component, Maven users will need to add the following
dependency to their `pom.xml`:
[source,xml]
----
@@ -80,7 +77,7 @@ The following table contains supported models in the model
zoo:
== DJL Engine implementation
-Because DJL is deep learning framework agnostic, you don't have to make a
choice between frameworks when creating your projects.
+Because DJL is deep learning framework-agnostic, you don't have to make a
choice between frameworks when creating your projects.
You can switch frameworks at any point.
To ensure the best performance, DJL also provides automatic CPU/GPU choice
based on hardware configuration.
@@ -193,7 +190,7 @@ from("file:/data/mnist/0/10.png")
=== Custom deep learning model
[source,java]
----
-// create deep learning model
+// create a deep learning model
Model model = Model.newInstance();
model.setBlock(new Mlp(28 * 28, 10, new int[]{128, 64}));
model.load(Paths.get(MODEL_DIR), MODEL_NAME);
