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Data · dataset · 2022

TinyShakespeare

Listed in Hugging Face Datasets

Description

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': 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) ```

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Text 75%
Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
Hugging Face Datasetskarpathy/tiny_shakespeare12 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].local:modality:textenrichment · Hugging Facekeyword-concept-rules@1.0.0title+description (75%)
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0