Referencias:
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:tiny_shakespeare')
- Descripción :
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)
- Licencia : Sin licencia conocida
- Versión : 1.0.0
- Divisiones :
| Separar | Ejemplos |
|---|---|
'test' | 1 |
'train' | 1 |
'validation' | 1 |
- Características :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}