| { | |
| "default": { | |
| "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': http://karpathy.github.io/2015/05/21/rnn-effectiveness/.\n\nTo use for e.g. character modelling:\n\n```\nd = datasets.load_dataset(name='tiny_shakespeare')['train']\nd = d.map(lambda x: datasets.Value('strings').unicode_split(x['text'], 'UTF-8'))\n# train split includes vocabulary for other splits\nvocabulary = sorted(set(next(iter(d)).numpy()))\nd = d.map(lambda x: {'cur_char': x[:-1], 'next_char': x[1:]})\nd = d.unbatch()\nseq_len = 100\nbatch_size = 2\nd = d.batch(seq_len)\nd = d.batch(batch_size)\n```\n", | |
| "citation": "@misc{\n author={Karpathy, Andrej},\n title={char-rnn},\n year={2015},\n howpublished={\\url{https://github.com/karpathy/char-rnn}}\n}", | |
| "homepage": "https://github.com/karpathy/char-rnn/blob/master/data/tinyshakespeare/input.txt", | |
| "license": "", | |
| "features": { | |
| "text": { | |
| "dtype": "string", | |
| "_type": "Value" | |
| } | |
| }, | |
| "builder_name": "tiny_shakespeare", | |
| "dataset_name": "tiny_shakespeare", | |
| "config_name": "default", | |
| "version": { | |
| "version_str": "1.0.0", | |
| "major": 1, | |
| "minor": 0, | |
| "patch": 0 | |
| }, | |
| "splits": { | |
| "train": { | |
| "name": "train", | |
| "num_bytes": 1003858, | |
| "num_examples": 1, | |
| "dataset_name": null | |
| }, | |
| "validation": { | |
| "name": "validation", | |
| "num_bytes": 55774, | |
| "num_examples": 1, | |
| "dataset_name": null | |
| }, | |
| "test": { | |
| "name": "test", | |
| "num_bytes": 55774, | |
| "num_examples": 1, | |
| "dataset_name": null | |
| } | |
| }, | |
| "download_size": 706067, | |
| "dataset_size": 1115406, | |
| "size_in_bytes": 1821473 | |
| } | |
| } |