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README.md
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@@ -35,9 +35,9 @@ How do you know which is the best ONNX model for you:
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- I don't know β Review this [guide](https://www.microsoft.com/en-us/windows/learning-center/how-to-check-gpu) to see whether you have a GPU in your Windows machine.
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- Yes β Access the Hugging Face DirectML ONNX models and instructions at [Phi-3-medium-4k-instruct-onnx-directml](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct-onnx-directml).
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- No β Do you have a NVIDIA GPU?
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- I don't know β Review this [guide](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html#verify-you-have-a-cuda-capable-gpu) to see whether you have a CUDA-capable GPU.
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Note: Using the Hugging Face CLI, you can download sub folders and not all models if you are limited on disk space. The FP16 model is recommended for larger batch sizes, while the INT4 model optimizes performance for lower batch sizes.
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- I don't know β Review this [guide](https://www.microsoft.com/en-us/windows/learning-center/how-to-check-gpu) to see whether you have a GPU in your Windows machine.
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- Yes β Access the Hugging Face DirectML ONNX models and instructions at [Phi-3-medium-4k-instruct-onnx-directml](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct-onnx-directml).
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- No β Do you have a NVIDIA GPU?
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- I don't know β Review this [guide](https://docs.nvidia.com/cuda/cuda-installation-guide-microsoft-windows/index.html#verify-you-have-a-cuda-capable-gpu) to see whether you have a CUDA-capable GPU.
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- Yes β Access the Hugging Face CUDA ONNX models and instructions at [Phi-3-medium-4k-instruct-onnx-cuda](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct-onnx-cuda) for NVIDIA GPUs.
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- No β Access the Hugging Face ONNX models for CPU devices and instructions at [Phi-3-medium-4k-instruct-onnx-cpu](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct-onnx-cpu)
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Note: Using the Hugging Face CLI, you can download sub folders and not all models if you are limited on disk space. The FP16 model is recommended for larger batch sizes, while the INT4 model optimizes performance for lower batch sizes.
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