minuscule_shakespeare

Références:

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:tiny_shakespeare')
  • Descriptif :
40,000 lines of Shakespeare from a variety of Shakespeare's plays. Featured in Andrej Karpathy's blog post 'The Unreasonable Effectiveness of Recurrent Neural Networks': http://karpathy.github.io/2015/05/21/rnn-effectiveness/.

To use for e.g. character modelling:


d = datasets.load_dataset(name='tiny_shakespeare')['train']
d = d.map(lambda x: datasets.Value('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)
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 1
'train' 1
'validation' 1
  • Caractéristiques :
{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}