Caffe2

Caffe2 helps researchers in Facebook train large machine learning models and deliver AI to mobile devicesmobile devices. Developers have access to different tools, enabling them to run large-scale distributed training scenarios and build machine learning applications for mobile using its cross-platform libraries.

Caffe2 is a deep learning framework. It was built on the original Caffe. itIt is lightweight, modular and scalable. It is an open source framework by Facebook.

Caffe2 is an open sourcea deep learning framework by Facebook. It was built on the original Caffe, designed with expression, speed and modularity in mind. Itit is lightweight, modular and scalable. It is an open source framework by Facebook.

Caffe2 helps researchers in Facebook train large machine learningmachine learning models and deliver AI to mobile devices. Developers have access to different tools, enabling them to run large-scale distributed training scenarios and build machine learning applications for mobile using its cross-platform libraries.

Caffe2 helphelps researchers in Facebook train large machine learning models and deliver AI to mobile devices. Developers have access to different tools, enabling them to run large-scale distributed training scenarios and build machine learning applications for mobile using its cross-platform libraries.

Caffe2 is an open source deep learning framework by Facebook. It was built on the original Caffe, designed with expression, speed and modularity in mind. It is lightweight, modular and scalable.

Caffe2 improves Caffe. It has first-class support for large-scale distributed training mobile deployment . It gives new hardware support in addition to CPU and CUDA. It is flexible for future operations such as quantized computation. It is stress tested by the vast scale of Facebook applications.

Caffe2 help researchers in Facebook train large machine learning models and deliver AI to mobile devices. Developers have access to different tools, enabling them to run large-scale distributed training scenarios and build machine learning applications for mobile using its cross-platform libraries.