chore(docs): add documentation for l4t images

Signed-off-by: Ettore Di Giacinto <[email protected]>
mudler · Jan 29, 2025 · 7f62b41 · 7f62b41
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diff --git a/docs/content/docs/getting-started/container-images.md b/docs/content/docs/getting-started/container-images.md
@@ -154,7 +154,7 @@ Images are available with and without python dependencies. Note that images with
 
 Images with `core` in the tag are smaller and do not contain any python dependencies. 
 
-{{< tabs tabTotal="7" >}}
+{{< tabs tabTotal="8" >}}
 {{% tab tabName="Vanilla / CPU Images" %}}
 
 | Description | Quay | Docker Hub                                   |
@@ -236,6 +236,18 @@ Images with `core` in the tag are smaller and do not contain any python dependen
 | Versioned image including FFMpeg, no python | `quay.io/go-skynet/local-ai:{{< version >}}-vulkan-fmpeg-core` | `localai/localai:{{< version >}}-vulkan-fmpeg-core`             |
 {{% /tab %}}
 
+{{% tab tabName="Nvidia Linux for tegra" %}}
+
+These images are compatible with Nvidia ARM64 devices, such as the Jetson Nano, Jetson Xavier NX, and Jetson AGX Xavier. For more information, see the [Nvidia L4T guide]({{%relref "docs/reference/nvidia-l4t" %}}).
+
+| Description | Quay | Docker Hub                                                  |
+| --- | --- |-------------------------------------------------------------|
+| Latest images from the branch (development) | `quay.io/go-skynet/local-ai:master-nvidia-l4t-arm64-core` | `localai/localai:master-nvidia-l4t-arm64-core`                      |
+| Latest tag | `quay.io/go-skynet/local-ai:latest-nvidia-l4t-arm64-core` | `localai/localai:latest-nvidia-l4t-arm64-core`                 |
+| Versioned image | `quay.io/go-skynet/local-ai:{{< version >}}-nvidia-l4t-arm64-core` | `localai/localai:{{< version >}}-nvidia-l4t-arm64-core`             |
+
+{{% /tab %}}
+
 {{< /tabs >}}
 
 ## See Also

diff --git a/docs/content/docs/reference/nvidia-l4t.md b/docs/content/docs/reference/nvidia-l4t.md
@@ -21,15 +21,21 @@ git clone https://github.com/mudler/LocalAI
 
 cd LocalAI
 
-docker build --build-arg SKIP_DRIVERS=true --build-arg BUILD_TYPE=cublas --build-arg BASE_IMAGE=nvcr.io/nvidia/l4t-jetpack:r36.4.0 --build-arg IMAGE_TYPE=core -t localai-orin .
+docker build --build-arg SKIP_DRIVERS=true --build-arg BUILD_TYPE=cublas --build-arg BASE_IMAGE=nvcr.io/nvidia/l4t-jetpack:r36.4.0 --build-arg IMAGE_TYPE=core -t quay.io/go-skynet/local-ai:master-nvidia-l4t-arm64-core .
+```
+
+Otherwise images are available on quay.io and dockerhub:
+
+```bash
+docker pull quay.io/go-skynet/local-ai:master-nvidia-l4t-arm64-core
 ```
 
 ## Usage
 
 Run the LocalAI container on Nvidia ARM64 devices using the following command, where `/data/models` is the directory containing the models:
 
 ```bash
-docker run -e DEBUG=true -p 8080:8080 -v /data/models:/build/models  -ti --restart=always --name local-ai --runtime nvidia --gpus all localai-orin
+docker run -e DEBUG=true -p 8080:8080 -v /data/models:/build/models  -ti --restart=always --name local-ai --runtime nvidia --gpus all quay.io/go-skynet/local-ai:master-nvidia-l4t-arm64-core
 ```
 
 Note: `/data/models` is the directory containing the models. You can replace it with the directory containing your models.