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README.md
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---
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license: llama3
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base_model: meta-llama/Meta-Llama-3-8B
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language:
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- en
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tags:
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- openchat
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- llama3
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- C-RLFT
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- ONNX
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- DML
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- DirectML
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- ONNXRuntime
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- conversational
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- custom_code
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pipeline_tag: text-generation
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---
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# openchat-3.6-8b-20240522 ONNX
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## Model Summary
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This repository contains the ONNX-optimized version of [openchat/openchat-3.6-8b-20240522](https://huggingface.co/openchat/openchat-3.6-8b-20240522), designed to accelerate inference using ONNX Runtime. These optimizations are specifically tailored for CPU and DirectML. DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning, offering GPU acceleration across a wide range of supported hardware and drivers, including those from AMD, Intel, NVIDIA, and Qualcomm.
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## Optimized Configurations
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The following optimized configurations are available:
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- **ONNX model for int4 DirectML:** Optimized for AMD, Intel, and NVIDIA GPUs on Windows, quantized to int4 using AWQ.
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- **ONNX model for int4 CPU and Mobile:** ONNX model for CPU and mobile using int4 quantization via RTN. There are two versions uploaded to balance latency vs. accuracy. Acc=1 is targeted at improved accuracy, while Acc=4 is for improved performance. For mobile devices, we recommend using the model with acc-level-4.
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## Usage
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### Installation and Setup
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To use the EmbeddedLLM/openchat-3.6-8b-20240522-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/openchat-3.6-8b-20240522-onnx --include="onnx/directml/*" --local-dir .\openchat-3.6-8b-20240522-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
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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 .\openchat-3.6-8b-20240522-onnx
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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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## Citation
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```
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@article{wang2023openchat,
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title={OpenChat: Advancing Open-source Language Models with Mixed-Quality Data},
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author={Wang, Guan and Cheng, Sijie and Zhan, Xianyuan and Li, Xiangang and Song, Sen and Liu, Yang},
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journal={arXiv preprint arXiv:2309.11235},
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year={2023}
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}
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```
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