InferLLM is a lightweight LLM model inference framework that mainly references and borrows from the llama.cpp project. llama.cpp puts almost all core code and kernels in a single file and use a large number of macros, making it difficult for developers to read and modify. InferLLM has the...
The framework for model inferenceNo Abstract available for this chapter.doi:10.1007/3-540-62927-0_10Shan-Hwei Nienhuys-ChengRoland WolfSpringer Berlin Heidelberg
摘要 过去一年,大型语言模型(LLM)的流行度不断增加。它们前所未有的规模和相关的高硬件成本阻碍了它们的广泛采用,需要高效的硬件设计。由于运行LLM推理所需的大型硬件,评估不同的硬件设计成为一个新的瓶颈。 …
nndeploy is an end-to-end model inference and deployment framework. It aims to provide users with a powerful, easy-to-use, high-performance, and mainstream framework compatible model inference and deployment experience.一款端到端的模型推理和部署框架。它
I've encountered similar error message when running the Jupyter Notebook for Model Inference with OpenVINO API using yolo-v4-tiny-tf model. For your information, that sample is only validated for classification models such as squeezenet1.1. However, yolo-v4-tiny-tf mo...
The samples/cplusplus/level2_simple_inference/1_classification/resnet50_imagenet_classification directory is used as the sample directory in this example. Prepare the ResNet-50 model. Obtain the original ResNet-50 model. Run the following command to create the caffe_model directory: mkdir -p caf...
This post provides a step-by-step tutorial for boosting your AI inference performance onAzure Machine Learningusing NVIDIA Triton Model Analyzer andONNX Runtime OLive, as shown in Figure 1. Figure 1. Workflow to optimize a PyTorch model using ONNX Runtime with OLive, Triton Model Analyzer, and...
the underlying model. For example, even though the framework model itself allows the second dimension to be any size, the model configuration could be specified asdims: [ 4, 4 ]. In this case, Triton would only accept inference requests where the input tensor’s shape was exactly[ 4, 4 ...
When a model is loaded by Triton the corresponding model framework initializes for that model. For some frameworks, some or all of this initialization is deferred until the model receives its first inference request (or first few inference requests). As a result, the first ...
inference engine for efficiently running any model converted to the ONNX format across different hardware and operating systems with minimum effort. Due to this framework interoperability nature of ONNX, ONNX Runtime improves the development efficiency from model training to inferen...