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fancyzhx/yelp_polarity

16,171 downloads in 30 days23 likesLast modified 8 Aug 2024View on Hugging Face
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The checks could not identify a recognised licence ID in the dataset's metadata.

  • Declared licenceNot declared in the tag or the card (see datasets with no declared licence)
  • Licence filesNo licence file at the top level of the repository
  • Declared sourcesNone listed in the card metadata
  • Access gated on Hugging FaceNo
not declarednot declareddeclared licenceno licence fileno licence filefound at top levelfancyzhx/yelp_polarityfancyzhx/yelp_pol…not declarednot declareddeclared licencefancyzhx/yelp_polarityfancyzhx/yelp_pol…no licence fileno licence filefound at top level

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Citation text from the card

@article{zhangCharacterlevelConvolutionalNetworks2015,
  archivePrefix = {arXiv},
  eprinttype = {arxiv},
  eprint = {1509.01626},
  primaryClass = {cs},
  title = {Character-Level {{Convolutional Networks}} for {{Text Classification}}},
  abstract = {This article offers an empirical exploration on the use of character-level convolutional networks (ConvNets) for text classification. We constructed several large-scale datasets to show that character-level convolutional networks could achieve state-of-the-art or competitive results. Comparisons are offered against traditional models such as bag of words, n-grams and their TFIDF variants, and deep learning models such as word-based ConvNets and recurrent neural networks.},
  journal = {arXiv:1509.01626 [cs]},
  author = {Zhang, Xiang and Zhao, Junbo and LeCun, Yann},
  month = sep,
  year = {2015},
}

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dataset_licence({ "id": "fancyzhx/yelp_polarity" })
signal: "unclear"
stated_licence: null
sources: 0

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