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README.md
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inference: false
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---
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# Phi-3-vision-128k-instruct ONNX
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This repository hosts the optimized versions of [microsoft/Phi-3-vision-128k-instruct](https://huggingface.co/microsoft/Phi-3-vision-128k-instruct/) to accelerate inference with DirectML and ONNX Runtime.
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4. **Download the model:**
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```sh
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huggingface-cli download EmbeddedLLM/Phi-3-vision-128k-instruct-onnx --include="onnx/
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```
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5. **Install necessary Python packages:**
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```sh
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pip install numpy==1.26.4
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pip install onnxruntime
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pip install --pre onnxruntime-genai
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```
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6. **Install Visual Studio 2015 runtime:**
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inference: false
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---
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# Phi-3-vision-128k-instruct ONNX models for CPU and CUDA
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This repository hosts the optimized versions of [microsoft/Phi-3-vision-128k-instruct](https://huggingface.co/microsoft/Phi-3-vision-128k-instruct/) to accelerate inference with ONNX Runtime.
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This repository is a clone from [microsoft/Phi-3-vision-128k-instruct-onnx-cpu](https://huggingface.co/microsoft/Phi-3-vision-128k-instruct-onnx-cpu), with extra files necessary for deploying the model with OpenAI-API-Compatible endpoints through [`embeddedllm`](https://github.com/EmbeddedLLM/embeddedllm) pypi library.
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## Usage on Windows (Intel / AMD / Nvidia / Qualcomm)
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```powershell
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conda create -n onnx python=3.10
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conda activate onnx
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winget install -e --id GitHub.GitLFS
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pip install huggingface-hub[cli]
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huggingface-cli download EmbeddedLLM/Phi-3-vision-128k-instruct-onnx --include='onnx/cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4' --local-dir .\Phi-3-vision-128k-instruct-onnx
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pip install numpy==1.26.4
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Invoke-WebRequest -Uri "https://raw.githubusercontent.com/microsoft/onnxruntime-genai/main/examples/python/phi3v.py" -OutFile "phi3v.py"
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pip install onnxruntime
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pip install --pre onnxruntime-genai==0.3.0rc2
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python phi3v.py -m .\Phi-3-vision-128k-instruct-onnx
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```
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# UPSTREAM README.md
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# Phi-3-vision-128k-instruct ONNX
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This repository hosts the optimized versions of [microsoft/Phi-3-vision-128k-instruct](https://huggingface.co/microsoft/Phi-3-vision-128k-instruct/) to accelerate inference with DirectML and ONNX Runtime.
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4. **Download the model:**
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```sh
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huggingface-cli download EmbeddedLLM/Phi-3-vision-128k-instruct-onnx --include="onnx/cpu_and_mobile/*" --local-dir .\Phi-3-vision-128k-instruct
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```
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5. **Install necessary Python packages:**
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```sh
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pip install numpy==1.26.4
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pip install onnxruntime
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pip install --pre onnxruntime-genai==0.3.0rc2
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```
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6. **Install Visual Studio 2015 runtime:**
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