Delete legacy JSON metadata (#3)

- Delete legacy JSON metadata (dddf50f813380313c9c2ab39cb29d8f201e8adf4)

dataset_infos.json

@@ -1 +0,0 @@
-{"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", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "tiny_shakespeare", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 55780, "num_examples": 1, "dataset_name": "tiny_shakespeare"}, "train": {"name": "train", "num_bytes": 1003864, "num_examples": 1, "dataset_name": "tiny_shakespeare"}, "validation": {"name": "validation", "num_bytes": 55780, "num_examples": 1, "dataset_name": "tiny_shakespeare"}}, "download_checksums": {"https://raw.githubusercontent.com/karpathy/char-rnn/master/data/tinyshakespeare/input.txt": {"num_bytes": 1115394, "checksum": "86c4e6aa9db7c042ec79f339dcb96d42b0075e16b8fc2e86bf0ca57e2dc565ed"}}, "download_size": 1115394, "dataset_size": 1115424, "size_in_bytes": 2230818}}