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docs/lora_optims.html
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<ul>
<li>One or more NVIDIA or AMD GPUs (in order to use the Triton kernels)
<ul>
<li>AMD can be used with experimental Triton support by setting the environment variable <code>TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL=1</code></li>
<li>Note: Set <code>TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL=1</code> to enable <a href="https://github.com/ROCm/aotriton/issues/16#issuecomment-2346675491">memory-efficient attention on AMD GPUs</a></li>
</ul></li>
<li>Targeted LoRA adapters cannot use Dropout
<ul>

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"title": "LoRA Optimizations",
"section": "Requirements",
"text": "Requirements\n\nOne or more NVIDIA or AMD GPUs (in order to use the Triton kernels)\n\nAMD can be used with experimental Triton support by setting the environment variable TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL=1\n\nTargeted LoRA adapters cannot use Dropout\n\nThis may limit model expressivity / cause overfitting\n\nTargeted LoRA adapters cannot have bias terms\n\nThis may limit model expressivity\n\n\nModels with pre-existing LoRA adapters that use Dropout or have bias terms may need to be re-finetuned without these features in order to be useful."
"text": "Requirements\n\nOne or more NVIDIA or AMD GPUs (in order to use the Triton kernels)\n\nNote: Set TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL=1 to enable memory-efficient attention on AMD GPUs\n\nTargeted LoRA adapters cannot use Dropout\n\nThis may limit model expressivity / cause overfitting\n\nTargeted LoRA adapters cannot have bias terms\n\nThis may limit model expressivity\n\n\nModels with pre-existing LoRA adapters that use Dropout or have bias terms may need to be re-finetuned without these features in order to be useful."
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