首先，使用LoRA对模型进行微调。不要使用QLoRA，因为它可能会导致后续合并过程中的精度损失。将适配器与P...
使用ONNX,您可以在不同的深度学习框架(如PyTorch和TensorFlow)之间无缝转换模型。 目前,ONNX微调可以使用Olive完成,但它还不支持LoRA。如果您想使用PyTorch进行LoRA微调,并使用ORT进行推理,如何实现? 首先,使用LoRA对模型进行微调。不要使用QLoRA,因为它可能会导致后续合并过程中的精度损失。 将适配器与PyTorch基础模型...
ONNX Runtime makes it easier for you to create amazing AI experiences on Windows and other platforms with less engineering effort and better performance. Olive simplifies the optimization process and eliminates the need for deep hardware knowledge. ONNX Runtime is the futu...
而且目前速度远远没有cuda快。目前微软做了个olive优化onnx提升directml速度,但是需要olive优化好的onnx资源,不是所有训练都会进行优化的,并且数据类型从float变int64(0~1=>0~255),改代码可能稍微麻烦些(不能直接copy)。总体来说不如cuda成熟,但优点是有的,潜力也是大的。 4.cpu 最慢但适用性最强,有些场景没想...
对Microsoft.Windows.Compatibility、Microsoft.ML.ImageAnalytics、Microsoft.ML.OnnxTransformer 和 Microsoft.ML.OnnxRuntime 重复这些步骤。 准备你的数据和预训练的模型 下载并解压缩项目资产目录 zip 文件。 将assets 目录复制到 ObjectDetection 项目目录中。 此目录及其子目录包含本教程所需的图像文件(Tiny YOLOv2...
Introducing ONNX Script: Authoring ONNX with the ease of Python ONNX Script is a new open-source library for directly authoring ONNX models in Python. News Tools PyTorch • June 26, 2023 • 4 min read Olive: A user-friendly toolchain for hardware-aware model optimization Introducing...
Full release notes for Olive v0.7.0 can be foundhere. Contributors Big thank you to the release manager@apsonawane, as well as@snnn,@jchen351,@sheetalarkadam, and everyone else who made this release possible! Tianlei Wu, Yi Zhang, Yulong Wang, Scott McKay, Edward Chen, Adrian Lizarraga...
traditional ONNX model . We can use Microsoft Olive to convert the DeepSeek-R1 Distrill model. Getting started with Microsoft Olive is very straightforward. Install the Microsoft Olive library through the command line and Python 3.10+ (recommended) pip install olive-ai The DeepSeek-R1 Distrill ...
We can quantize and convert it to an ONNX model for CPU inference through Microsoft Olive. Of course, it can also be converted to a model for GPU inference. Here I take the 14B DeepSeek-R1-Distill-Qwen-14B as an example and make an inference comparison with Microsoft's Phi-4-14B ...
对Microsoft.Windows.Compatibility、Microsoft.ML.ImageAnalytics、Microsoft.ML.OnnxTransformer 和 Microsoft.ML.OnnxRuntime 重复这些步骤。准备你的数据和预训练的模型下载并解压缩项目资产目录 zip 文件。 将assets 目录复制到 ObjectDetection 项目目录中。 此目录及其子目录包含本教程所需的图像文件(Tiny YOLOv2 模...