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use 3.12

use 1.19.2
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mertalev
2024-12-19 20:53:40 -05:00
parent f30fac971a
commit d9a41b8ea0
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docs/docs/features/ml-hardware-acceleration.md
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@@ -11,7 +11,7 @@ You do not need to redo any machine learning jobs after enabling hardware accele
- ARM NN (Mali)
- CUDA (NVIDIA GPUs with [compute capability](https://developer.nvidia.com/cuda-gpus) 5.2 or higher)
- ROCM (AMD GPUs)
- ROCm (AMD GPUs)
- OpenVINO (Intel GPUs such as Iris Xe and Arc)
## Limitations
@@ -42,9 +42,9 @@ You do not need to redo any machine learning jobs after enabling hardware accele
- The installed driver must be >= 535 (it must support CUDA 12.2).
- On Linux (except for WSL2), you also need to have [NVIDIA Container Toolkit][nvct] installed.
#### ROCM
#### ROCm
- The GPU must be supported by ROCM (or use `HSA_OVERRIDE_GFX_VERSION=<a supported version, ie 10.3.0>`)
- The GPU must be supported by ROCm. If it isn't officially supported, you can attempt to use the `HSA_OVERRIDE_GFX_VERSION` environmental variable: `HSA_OVERRIDE_GFX_VERSION=<a supported version, e.g. 10.3.0>`.
#### OpenVINO