Update README.md

README.md

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 [Phi4-mini](https://huggingface.co/microsoft/Phi-4-mini-instruct) is quantized by the PyTorch team using [torchao](https://huggingface.co/docs/transformers/main/en/quantization/torchao) with 8-bit embeddings and 8-bit dynamic activations with 4-bit weight linears (8da4w).
 The model is suitable for mobile deployment with [ExecuTorch](https://github.com/pytorch/executorch).
 
-The quantized model can be exported to an ExecuTorch pte file, see [Exporting to ExecuTorch](#exporting-to-executorch).  We also provide the [quantized pte](https://huggingface.co/pytorch/Phi-4-mini-instruct-8da4w/blob/main/phi4-mini-8da4w.pte) for direct use.  
+See [Exporting to ExecuTorch](#exporting-to-executorch) for exporting the quantized model to an ExecuTorch pte file.  We also provide the [quantized pte](https://huggingface.co/pytorch/Phi-4-mini-instruct-8da4w/blob/main/phi4-mini-8da4w.pte) for direct use.  
 
 # Running in a mobile app
 The [PTE file](https://huggingface.co/pytorch/Phi-4-mini-instruct-8da4w/blob/main/phi4-mini-8da4w.pte) can be run with ExecuTorch on a mobile phone.  See the [instructions](https://pytorch.org/executorch/main/llm/llama-demo-ios.html) for doing this in iOS.