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ovms doc fix (#2988)

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* added OpenVINO Model Server

* ovms doc fixes
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Trawinski, Dariusz 2020-11-05 19:19:54 +01:00 committed by GitHub
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docs/model_server/README.md
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@ -11,7 +11,7 @@ The server implements gRPC and REST API framework with data serialization and de
OVMS is now implemented in C++ and provides much higher scalability compared to its predecessor in the Python version. OVMS is now implemented in C++ and provides much higher scalability compared to its predecessor in the Python version.
You can take advantage of all the power of Xeon® CPU capabilities or AI accelerators and expose it over the network interface. You can take advantage of all the power of Xeon® CPU capabilities or AI accelerators and expose it over the network interface.
Read the [release notes](https://github.com/openvinotoolkit/model_server/blob/main/releases) to find out what's new in the C++ version. Read the [release notes](https://github.com/openvinotoolkit/model_server/releases) to find out what's new in the C++ version.
Review the [Architecture Concept](https://github.com/openvinotoolkit/model_server/blob/main/docs/architecture.md) document for more details. Review the [Architecture Concept](https://github.com/openvinotoolkit/model_server/blob/main/docs/architecture.md) document for more details.
@ -26,7 +26,7 @@ A few key features:
- [Model reshaping](https://github.com/openvinotoolkit/model_server/blob/main/docs/docker_container.md#model-reshaping). The server supports reshaping models in runtime. - [Model reshaping](https://github.com/openvinotoolkit/model_server/blob/main/docs/docker_container.md#model-reshaping). The server supports reshaping models in runtime.
- [Model ensemble](https://github.com/openvinotoolkit/model_server/blob/main/docs/ensemble_scheduler.md) (preview). Connect multiple models to deploy complex processing solutions and reduce overhead of sending data back and forth. - [Model ensemble](https://github.com/openvinotoolkit/model_server/blob/main/docs/ensemble_scheduler.md) (preview). Connect multiple models to deploy complex processing solutions and reduce overhead of sending data back and forth.
> **NOTE**: OVMS has been tested on CentOS\* and Ubuntu\*. Publically released Docker images are based on CentOS. > **NOTE**: OVMS has been tested on CentOS\* and Ubuntu\*. Publically released [Docker images](https://hub.docker.com/r/openvino/model_server) are based on CentOS.
## Build OpenVINO Model Server ## Build OpenVINO Model Server
@ -125,6 +125,8 @@ REST API is recommended when the primary goal is in reducing the number of clien
## References ## References
* [Speed and Scale AI Inference Operations Across Multiple Architectures - webinar recording](https://techdecoded.intel.io/essentials/speed-and-scale-ai-inference-operations-across-multiple-architectures/)
* [OpenVINO™](https://software.intel.com/en-us/openvino-toolkit) * [OpenVINO™](https://software.intel.com/en-us/openvino-toolkit)
* [TensorFlow Serving](https://github.com/tensorflow/serving) * [TensorFlow Serving](https://github.com/tensorflow/serving)
@ -133,9 +135,8 @@ REST API is recommended when the primary goal is in reducing the number of clien
* [RESTful API](https://restfulapi.net/) * [RESTful API](https://restfulapi.net/)
* [Inference at scale in Kubernetes](https://www.intel.ai/inference-at-scale-in-kubernetes) * [Inference at Scale in Kubernetes](https://www.intel.ai/inference-at-scale-in-kubernetes)
* [OpenVINO Model Server boosts AI](https://www.intel.ai/openvino-model-server-boosts-ai-inference-operations/)
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