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chore(docs): add documentation for l4t images

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Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto 2025-01-29 15:16:07 +01:00
parent 1f4e66d638
commit 7f62b418a4
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14
docs/content/docs/getting-started/container-images.md
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@ -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

10
docs/content/docs/reference/nvidia-l4t.md
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@ -21,7 +21,13 @@ 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
@ -29,7 +35,7 @@ docker build --build-arg SKIP_DRIVERS=true --build-arg BUILD_TYPE=cublas --build
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.