The most heavily tested versions are 1.13.1, 1.15, and 2.2 TensorRT In general, you can choose any version of TensorFlow as long as it works with a supported version of CUDA. Below, however, we do discuss the frameworks we use to test Bitfusion. This page discusses the versions, models, and products that are compatible with Bitfusion 2.5.1 and 2.5.1.īitfusion is not designed for specific frameworks. provides an interface, on Linux, called Resource Manager) Hardware driver (NVIDIA driver, nvidia.ko.AI/ML and other libraries (examples include CuDNN, CUBLAS, CUDA runtime driver).Framework (examples include TensorFlow and PyTorch).In bullet form, this stack might look like the following: ![]() Bitfusion works with the hardware and software stack of AI/ML environments and applications.
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