AI inference acceleration supports a variety of frameworks and models, including but not limited to TensorFlow, PyTorch, Keras, ONNX, and various deep learning models such as CNN (Convolutional Neural Networks), RNN (Recurrent Neural Networks), and LSTM (Long Short-Term Memory) networks.
For example, TensorFlow and PyTorch are popular open-source frameworks for developing and training deep learning models. AI inference acceleration can optimize the inference process of models trained with these frameworks, significantly improving their performance on edge devices or in cloud environments.
ONNX (Open Neural Network Exchange) is an open format for representing deep learning models, which allows models trained in different frameworks to be shared and used across platforms. AI inference acceleration can support ONNX models, enabling efficient inference on a wide range of hardware.
When it comes to cloud services, Tencent Cloud provides a comprehensive suite of AI inference acceleration solutions. For instance, Tencent Cloud's AI Inference Accelerator leverages advanced hardware acceleration technologies to deliver high-performance inference capabilities for various deep learning models. It supports popular frameworks like TensorFlow, PyTorch, and ONNX, making it easier for developers to deploy and scale their AI applications on the cloud.