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feat: docs.immich.app (#21819)

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Co-authored-by: Jason Rasmussen <jason@rasm.me>
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Zack Pollard
2025-09-25 15:54:34 +01:00
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docs/docs/guides/remote-machine-learning.md
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# Remote Machine Learning
To alleviate [performance issues on low-memory systems](/docs/FAQ.mdx#why-is-immich-slow-on-low-memory-systems-like-the-raspberry-pi) like the Raspberry Pi, you may also host Immich's machine learning container on a more powerful system, such as your laptop or desktop computer. The server container will send requests containing the image preview to the remote machine learning container for processing. The machine learning container does not persist this data or associate it with a particular user.
To alleviate [performance issues on low-memory systems](/FAQ.mdx#why-is-immich-slow-on-low-memory-systems-like-the-raspberry-pi) like the Raspberry Pi, you may also host Immich's machine learning container on a more powerful system, such as your laptop or desktop computer. The server container will send requests containing the image preview to the remote machine learning container for processing. The machine learning container does not persist this data or associate it with a particular user.
:::info
Smart Search and Face Detection will use this feature, but Facial Recognition will not. This is because Facial Recognition uses the _outputs_ of these models that have already been saved to the database. As such, its processing is between the server container and the database.
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2. Copy the following `docker-compose.yml` to the remote server
:::info
If using hardware acceleration, the [hwaccel.ml.yml](https://github.com/immich-app/immich/releases/latest/download/hwaccel.ml.yml) file also needs to be added and the `docker-compose.yml` needs to be configured as described in the [hardware acceleration documentation](/docs/features/ml-hardware-acceleration)
If using hardware acceleration, the [hwaccel.ml.yml](https://github.com/immich-app/immich/releases/latest/download/hwaccel.ml.yml) file also needs to be added and the `docker-compose.yml` needs to be configured as described in the [hardware acceleration documentation](/features/ml-hardware-acceleration)
:::
```yaml