lm1b

A benchmark corpus to be used for measuring progress in statistical language modeling. This has almost one billion words in the training data.

• URL: http://www.statmt.org/lm-benchmark/
• DatasetBuilder: tfds.text.lm1b.Lm1b

lm1b is configured with tfds.text.lm1b.Lm1bConfig and has the following configurations predefined (defaults to the first one):

• plain_text (v0.0.1) (Size: 1.67 GiB): Plain text

• bytes (v0.0.1) (Size: 1.67 GiB): Uses byte-level text encoding with tfds.features.text.ByteTextEncoder

• subwords8k (v0.0.2) (Size: 1.67 GiB): Uses tfds.features.text.SubwordTextEncoder with 8k vocab size

• subwords32k (v0.0.2) (Size: 1.67 GiB): Uses tfds.features.text.SubwordTextEncoder with 32k vocab size

lm1b/plain_text

Plain text

Versions:

• 0.0.1 (default):
• 1.0.0: New split API (https://tensorflow.org/datasets/splits)

Statistics

Features

FeaturesDict({
    'text': Text(shape=(), dtype=tf.string),
})

Urls

• http://www.statmt.org/lm-benchmark/

Supervised keys (for as_supervised=True)

(u'text', u'text')

lm1b/bytes

Uses byte-level text encoding with tfds.features.text.ByteTextEncoder

Versions:

• 0.0.1 (default):
• 1.0.0: New split API (https://tensorflow.org/datasets/splits)

Statistics

Features

FeaturesDict({
    'text': Text(shape=(None,), dtype=tf.int64, encoder=<ByteTextEncoder vocab_size=257>),
})

Urls

• http://www.statmt.org/lm-benchmark/

Supervised keys (for as_supervised=True)

(u'text', u'text')

lm1b/subwords8k

Uses tfds.features.text.SubwordTextEncoder with 8k vocab size

Versions:

• 0.0.2 (default):
• 1.0.0: New split API (https://tensorflow.org/datasets/splits)

Statistics

Features

FeaturesDict({
    'text': Text(shape=(None,), dtype=tf.int64, encoder=<SubwordTextEncoder vocab_size=8189>),
})

Urls

• http://www.statmt.org/lm-benchmark/

Supervised keys (for as_supervised=True)

(u'text', u'text')

lm1b/subwords32k

Uses tfds.features.text.SubwordTextEncoder with 32k vocab size

Versions:

• 0.0.2 (default):
• 1.0.0: New split API (https://tensorflow.org/datasets/splits)

Statistics

Features

FeaturesDict({
    'text': Text(shape=(None,), dtype=tf.int64, encoder=<SubwordTextEncoder vocab_size=32711>),
})

Urls

• http://www.statmt.org/lm-benchmark/

Supervised keys (for as_supervised=True)

(u'text', u'text')

Citation

@article{DBLP:journals/corr/ChelbaMSGBK13,
  author    = {Ciprian Chelba and
               Tomas Mikolov and
               Mike Schuster and
               Qi Ge and
               Thorsten Brants and
               Phillipp Koehn},
  title     = {One Billion Word Benchmark for Measuring Progress in Statistical Language
               Modeling},
  journal   = {CoRR},
  volume    = {abs/1312.3005},
  year      = {2013},
  url       = {http://arxiv.org/abs/1312.3005},
  archivePrefix = {arXiv},
  eprint    = {1312.3005},
  timestamp = {Mon, 13 Aug 2018 16:46:16 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/corr/ChelbaMSGBK13},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}