Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms   We present Fashion-MNIST, a new dataset comprising of 28x28 grayscale images
of 70,000 fashion products from 10 categories, with 7,000 images per category.
The training set has 60,000 images and the test set has 10,000 images.
Fashion-MNIST is intended to serve as a direct drop-in replacement for the
original MNIST dataset for benchmarking machine learning algorithms, as it
shares the same image size, data format and the structure of training and
testing splits. The dataset is freely available at
https://github.com/zalandoresearch/fashion-mnist

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The categories of this paper are: astro-ph
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The categories of this paper are: q-fin
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The categories of this paper are: econ
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The categories of this paper are: quant-ph
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The categories of this paper are: atom-ph
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The categories of this paper are: nlin
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-ex
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The categories of this paper are: mtrl-th
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The categories of this paper are: cmp-lg
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The categories of this paper are: gr-qc
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The categories of this paper are: q-bio
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The categories of this paper are: math
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The categories of this paper are: physics
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The categories of this paper are: adap-org
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The categories of this paper are: alg-geom