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简体中文 | English
FastDeploy builds an end-to-end serving deployment based on Triton Inference Server. The underlying backend uses the FastDeploy high-performance Runtime module and integrates the FastDeploy pre- and post-processing modules to achieve end-to-end serving deployment. It can achieve fast deployment with easy-to-use process and excellent performance.
FastDeploy also provides an easy-to-use Python service deployment method, refer PaddleSeg deployment example for its usage.
CPU images only support Paddle/ONNX models for serving deployment on CPUs, and supported inference backends include OpenVINO, Paddle Inference, and ONNX Runtime
docker pull registry.baidubce.com/paddlepaddle/fastdeploy:1.0.7-cpu-only-21.10
GPU images support Paddle/ONNX models for serving deployment on GPU and CPU, and supported inference backends including OpenVINO, TensorRT, Paddle Inference, and ONNX Runtime
docker pull registry.baidubce.com/paddlepaddle/fastdeploy:1.0.7-gpu-cuda11.4-trt8.5-21.10
Users can also compile the image by themselves according to their own needs, referring to the following documents:
Task | Model |
---|---|
Classification | PaddleClas |
Detection | PaddleDetection |
Detection | ultralytics/YOLOv5 |
NLP | PaddleNLP/ERNIE-3.0 |
NLP | PaddleNLP/UIE |
Speech | PaddleSpeech/PP-TTS |
OCR | PaddleOCR/PP-OCRv3 |
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Dear OpenI User
Thank you for your continuous support to the Openl Qizhi Community AI Collaboration Platform. In order to protect your usage rights and ensure network security, we updated the Openl Qizhi Community AI Collaboration Platform Usage Agreement in January 2024. The updated agreement specifies that users are prohibited from using intranet penetration tools. After you click "Agree and continue", you can continue to use our services. Thank you for your cooperation and understanding.
For more agreement content, please refer to the《Openl Qizhi Community AI Collaboration Platform Usage Agreement》