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openchat-3.6-8b-20240522 ONNX

Model Summary

This repository contains the ONNX-optimized version of 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.

Optimized Configurations

The following optimized configurations are available:

  • ONNX model for int4 DirectML: Optimized for AMD, Intel, and NVIDIA GPUs on Windows, quantized to int4 using AWQ.
  • 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.

Usage

Installation and Setup

To use the EmbeddedLLM/openchat-3.6-8b-20240522-onnx model on Windows with DirectML, follow these steps:

  1. Create and activate a Conda environment:
conda create -n onnx python=3.10
conda activate onnx
  1. Install Git LFS:
winget install -e --id GitHub.GitLFS
  1. Install Hugging Face CLI:
pip install huggingface-hub[cli]
  1. Download the model:
huggingface-cli download EmbeddedLLM/openchat-3.6-8b-20240522-onnx --include="onnx/directml/*" --local-dir .\openchat-3.6-8b-20240522-onnx
  1. Install necessary Python packages:
pip install numpy==1.26.4
pip install onnxruntime-directml
pip install --pre onnxruntime-genai-directml
  1. Install Visual Studio 2015 runtime:
conda install conda-forge::vs2015_runtime
  1. Download the example script:
Invoke-WebRequest -Uri "https://raw.githubusercontent.com/microsoft/onnxruntime-genai/main/examples/python/phi3-qa.py" -OutFile "phi3-qa.py"
  1. Run the example script:
python phi3-qa.py -m .\openchat-3.6-8b-20240522-onnx

Hardware Requirements

Minimum Configuration:

  • Windows: DirectX 12-capable GPU (AMD/Nvidia)
  • CPU: x86_64 / ARM64

Tested Configurations:

  • GPU: AMD Ryzen 8000 Series iGPU (DirectML)
  • CPU: AMD Ryzen CPU

Citation

@article{wang2023openchat,
  title={OpenChat: Advancing Open-source Language Models with Mixed-Quality Data},
  author={Wang, Guan and Cheng, Sijie and Zhan, Xianyuan and Li, Xiangang and Song, Sen and Liu, Yang},
  journal={arXiv preprint arXiv:2309.11235},
  year={2023}
}
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