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Delete legacy dataset_infos.json
Browse files- dataset_infos.json +0 -46
dataset_infos.json
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{
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"default": {
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"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",
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"citation": "@misc{\n author={Karpathy, Andrej},\n title={char-rnn},\n year={2015},\n howpublished={\\url{https://github.com/karpathy/char-rnn}}\n}",
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"homepage": "https://github.com/karpathy/char-rnn/blob/master/data/tinyshakespeare/input.txt",
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"license": "",
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"features": {
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"text": {
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"dtype": "string",
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"_type": "Value"
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}
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},
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"builder_name": "tiny_shakespeare",
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"dataset_name": "tiny_shakespeare",
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"config_name": "default",
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"version": {
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"version_str": "1.0.0",
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"major": 1,
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"minor": 0,
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"patch": 0
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},
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"splits": {
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"train": {
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"name": "train",
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"num_bytes": 1003858,
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"num_examples": 1,
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"dataset_name": null
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},
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"validation": {
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"name": "validation",
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"num_bytes": 55774,
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"num_examples": 1,
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"dataset_name": null
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},
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"test": {
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"name": "test",
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"num_bytes": 55774,
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"num_examples": 1,
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"dataset_name": null
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}
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},
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"download_size": 706067,
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"dataset_size": 1115406,
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"size_in_bytes": 1821473
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}
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}
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