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PyTorch-Transformers (formerly known as pytorch-pretrained-bert) is a library of state-of-the-art pre-trained models for Natural Language Processing (NLP). The library currently contains PyTorch implementations, pre-trained model weights, usage scripts and conversion utilities for the following models:

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Compile PyTorch Object Detection Models¶. This article is an introductory tutorial to deploy PyTorch object detection models with Relay VM. For us to begin with, PyTorch should be installed.

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Jun 09, 2020 · PyTorch is a Python language code library that can be used to create deep neural networks. The fundamental object in PyTorch is called a tensor. A tensor is essentially an n-dimensional array that can be processed using either a CPU or a GPU. PyTorch tensors are surprisingly complex.

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May 30, 2020 · Pytorch is a framework for deep learning which is very popular among researchers. There are other popular frameworks too like TensorFlow and MXNet. In this article, we will majorly focus on the...

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A PyTorch tensor is an n -dimensional array, similar to NumPy arrays. If you are familiar with NumPy, you will see a similarity in the syntax when working with tensors, as shown in the following table: In this recipe, you will learn how to define and change tensors, convert tensors into arrays, and move them between computing devices.

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Torch tensors are effectively an extension of the numpy.array object. Tensors are an essential conceptual component in deep learning systems, so having a good understanding of how they work is important. In our first example, we will be looking at tensors of size 2 x 3. In PyTorch, we can create tensors in the same way that we create NumPy arrays.

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