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docs(ml): update link (#9477)

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update link
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docs/docs/features/hardware-transcoding.md
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@ -33,7 +33,7 @@ You do not need to redo any transcoding jobs after enabling hardware acceleratio
#### NVENC #### NVENC
- You must have the official NVIDIA driver installed on the server. - You must have the official NVIDIA driver installed on the server.
- On Linux (except for WSL2), you also need to have [NVIDIA Container Runtime][nvcr] installed. - On Linux (except for WSL2), you also need to have [NVIDIA Container Toolkit][nvct] installed.
#### QSV #### QSV
@ -122,7 +122,7 @@ Once this is done, you can continue to step 3 of "Basic Setup".
- While you can use VAAPI with NVIDIA and Intel devices, prefer the more specific APIs since they're more optimized for their respective devices - While you can use VAAPI with NVIDIA and Intel devices, prefer the more specific APIs since they're more optimized for their respective devices
[hw-file]: https://github.com/immich-app/immich/releases/latest/download/hwaccel.transcoding.yml [hw-file]: https://github.com/immich-app/immich/releases/latest/download/hwaccel.transcoding.yml
[nvcr]: https://github.com/NVIDIA/nvidia-container-runtime/ [nvct]: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
[jellyfin-lp]: https://jellyfin.org/docs/general/administration/hardware-acceleration/intel/#configure-and-verify-lp-mode-on-linux [jellyfin-lp]: https://jellyfin.org/docs/general/administration/hardware-acceleration/intel/#configure-and-verify-lp-mode-on-linux
[jellyfin-kernel-bug]: https://jellyfin.org/docs/general/administration/hardware-acceleration/intel/#known-issues-and-limitations [jellyfin-kernel-bug]: https://jellyfin.org/docs/general/administration/hardware-acceleration/intel/#known-issues-and-limitations
[libmali-rockchip]: https://github.com/tsukumijima/libmali-rockchip/releases [libmali-rockchip]: https://github.com/tsukumijima/libmali-rockchip/releases

4
docs/docs/features/ml-hardware-acceleration.md
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@ -38,7 +38,7 @@ You do not need to redo any machine learning jobs after enabling hardware accele
- The GPU must have compute capability 5.2 or greater. - The GPU must have compute capability 5.2 or greater.
- The server must have the official NVIDIA driver installed. - The server must have the official NVIDIA driver installed.
- The installed driver must be >= 535 (it must support CUDA 12.2). - The installed driver must be >= 535 (it must support CUDA 12.2).
- On Linux (except for WSL2), you also need to have [NVIDIA Container Runtime][nvcr] installed. - On Linux (except for WSL2), you also need to have [NVIDIA Container Toolkit][nvct] installed.
#### OpenVINO #### OpenVINO
@ -99,7 +99,7 @@ You can confirm the device is being recognized and used by checking its utilizat
::: :::
[hw-file]: https://github.com/immich-app/immich/releases/latest/download/hwaccel.ml.yml [hw-file]: https://github.com/immich-app/immich/releases/latest/download/hwaccel.ml.yml
[nvcr]: https://github.com/NVIDIA/nvidia-container-runtime/ [nvct]: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
## Tips ## Tips