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README.md
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---
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license: apache-2.0
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pipeline_tag: text-generation
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tags:
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- ONNX
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- DML
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- DirectML
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- ONNXRuntime
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- mistral
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- conversational
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- custom_code
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inference: false
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---
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# Mistral-7B-Instruct-v0.3 ONNX
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## Model Summary
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The [Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) is an optimized version of the Mistral-7B model, fine-tuned for instruction-based tasks. This model is available in ONNX format to accelerate inference using ONNX Runtime, specifically optimized for CPU and DirectML. DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning, providing GPU acceleration for a wide range of supported hardware and drivers, including AMD, Intel, NVIDIA, and Qualcomm GPUs.
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## Model Description
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- **Developed by:** Mistral AI
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- **Model type:** ONNX
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- **Language(s) (NLP):** Python, C, C++
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- **License:** Apache License Version 2.0
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- **Model Description:** This model is a conversion of the Mistral-7B-Instruct-v0.3 for ONNX Runtime inference, optimized for CPU and DirectML.
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## Usage
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### Installation and Setup
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To use the Mistral-7B-Instruct-v0.3 ONNX model on Windows with DirectML, follow these steps:
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1. **Create and activate a Conda environment:**
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```sh
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conda create -n onnx python=3.10
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conda activate onnx
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```
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2. **Install Git LFS:**
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```sh
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winget install -e --id GitHub.GitLFS
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```
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3. **Install Hugging Face CLI:**
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```sh
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pip install huggingface-hub[cli]
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```
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4. **Download the model:**
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```sh
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huggingface-cli download EmbeddedLLM/mistral-7b-instruct-v0.3-int4-onnx-directml --include directml/* --local-dir .\mistral-7b-instruct-v0.3
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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
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pip install onnxruntime-directml
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pip install --pre onnxruntime-genai-directml
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```
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6. **Install Visual Studio 2015 runtime:**
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```sh
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conda install conda-forge::vs2015_runtime
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```
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7. **Download the example script:**
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```sh
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Invoke-WebRequest -Uri "https://raw.githubusercontent.com/microsoft/onnxruntime-genai/main/examples/python/phi3-qa.py" -OutFile "phi3-qa.py"
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```
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8. **Run the example script:**
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```sh
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python phi3-qa.py -m .\mistral-7b-instruct-v0.3
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```
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### Hardware Requirements
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- **Minimum Configuration:**
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- **Windows:** DirectX 12-capable GPU (AMD/Nvidia)
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- **CPU:** x86_64 / ARM64
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- **Tested Configurations:**
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- **GPU:** AMD Ryzen 8000 Series iGPU (DirectML)
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- **CPU:** AMD Ryzen CPU
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## Optimized Configurations
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The following optimized configurations are available:
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1. **ONNX model for int4 DML:** Optimized for AMD, Intel, and NVIDIA GPUs on Windows, quantized to int4.
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2. **ONNX model for int4 CPU:** Optimized for CPU, using int4 quantization.
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