tiny_shakespeare

• Deskripsi :

40.000 baris Shakespeare dari berbagai drama Shakespeare. Ditampilkan di entri blog Andrej Karpathy 'The Unreasonable Effectiveness of Recurrent Neural Networks': http://karpathy.github.io/2015/05/21/rnn-effectiveness/

Untuk digunakan misalnya untuk pemodelan karakter:

d = tfds.load(name='tiny_shakespeare')['train']
d = d.map(lambda x: tf.strings.unicode_split(x['text'], 'UTF-8'))
# train split includes vocabulary for other splits
vocabulary = sorted(set(next(iter(d)).numpy()))
d = d.map(lambda x: {'cur_char': x[:-1], 'next_char': x[1:]})
d = d.unbatch()
seq_len = 100
batch_size = 2
d = d.batch(seq_len)
d = d.batch(batch_size)

• Beranda : https://github.com/karpathy/char-rnn/blob/master/data/tinyshakespeare/input.txt

• Kode sumber : tfds.text.TinyShakespeare

• Versi :

  • 1.0.0 (default): Tidak ada catatan rilis.

• Ukuran unduhan : Unknown size

• Ukuran set data : 1.06 MiB

• Cache otomatis ( dokumentasi ): Ya

• Split :

• Fitur :

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

• Kunci yang diawasi (Lihat as_supervised doc ): None

• Kutipan :

@misc{
  author={Karpathy, Andrej},
  title={char-rnn},
  year={2015},
  howpublished={\url{https://github.com/karpathy/char-rnn} }
}

• Gambar ( tfds.show_examples ): Tidak didukung.

• Contoh ( tfds.as_dataframe ):