Team Ai
Datasetpublic

OpenScientificCodeRegistry/Database

Open Scientific Code Registry (OSCR): the authors' scripts The code published by the authors of open-access neuroscience papers, as found and verified by Open Scientific Code Registry (OSCR). Each file is here exactly as it is at the source, at the verified commit, under the license of its repository. 421,275 unique files (3,782 MB of text) from 8,849 repositories, in 24 Parquet block(s). Only files whose repository's license allows redistribution, confirmed by the repository's… See the full description on the dataset page: https://huggingface.co/datasets/OpenScientificCodeRegistry/Database.

sourceHugging Faceotherupdated 2d agoView on Hugging Face
0likes5.6kdownloads
github.com__jvparidon__subs2vec.json237 linesDownload Raw Back to ba
1{2 "format": "oscr-script-manifest/1",3 "repository": "github.com/jvparidon/subs2vec",4 "url": "https://github.com/jvparidon/subs2vec",5 "host": "github.com",6 "commit": "adb9e72b64dc6dbde3c2060ee0d3964ab623a149",7 "license": "MIT",8 "license_confirmed_by": "license file LICENSE.md",9 "redistribution": "yes",10 "files": [11  {12   "path": "LICENSE.md",13   "sha256": "f915398362f4985b9aebe3f09c7a2008fc409c085844ed679504c695b9326acd",14   "language": "License",15   "lines": 21,16   "truncated": false,17   "block": 10,18   "row": 612719  },20  {21   "path": "README.md",22   "sha256": "b8c692a389373c2c28a5d08f50ee6ec5b270d61cf1e7081183bb76b21541acd3",23   "language": "Text",24   "lines": 241,25   "truncated": false,26   "block": 10,27   "row": 2003228  },29  {30   "path": "docs/conf.py",31   "sha256": "fee84d57399cde6098def111ac542ef235192b754d8c83567ac994353b0d0f73",32   "language": "Python",33   "lines": 57,34   "truncated": false,35   "block": 10,36   "row": 1184837  },38  {39   "path": "setup.py",40   "sha256": "6c6efb78570d0ddd960b03f1aa477d25d5c32bd1825e1013aaa2e117eb610da6",41   "language": "Python",42   "lines": 40,43   "truncated": false,44   "block": 10,45   "row": 1084646  },47  {48   "path": "subs2vec/__init__.py",49   "sha256": "e5f7bd63b0c3cce6e47a1b1bbe4f676271baa5100a25e3c6315a4c974081f358",50   "language": "Python",51   "lines": 10,52   "truncated": false,53   "block": 10,54   "row": 1012555  },56  {57   "path": "subs2vec/analogies.py",58   "sha256": "1fd6602f4b787eaaeeb3c47c1a41b43cdecf2dfcdc66d5c1bd12dbb84871c702",59   "language": "Python",60   "lines": 183,61   "truncated": false,62   "block": 10,63   "row": 1535164  },65  {66   "path": "subs2vec/clean_other.py",67   "sha256": "1d2d29338d43158de4a22bafb59276b91db15ee4ebb264ae13ee8db9707587fd",68   "language": "Python",69   "lines": 113,70   "truncated": false,71   "block": 10,72   "row": 1377173  },74  {75   "path": "subs2vec/clean_subs.py",76   "sha256": "e22e8811cb3b9077396df51c92d9b4f167b14333e72c368a27019a9d7ff7085a",77   "language": "Python",78   "lines": 176,79   "truncated": false,80   "block": 10,81   "row": 1466582  },83  {84   "path": "subs2vec/clean_wiki.py",85   "sha256": "8129538a4d54652056169d2e783847b326ba2a3a29de5a8d580f7d1346e3fe6f",86   "language": "Python",87   "lines": 140,88   "truncated": false,89   "block": 10,90   "row": 1412391  },92  {93   "path": "subs2vec/count_words.py",94   "sha256": "d51b7aa1faa57f74d40b8195ff1ef0416327954ea5643a4f130157cb36995722",95   "language": "Python",96   "lines": 45,97   "truncated": false,98   "block": 10,99   "row": 11327100  },101  {102   "path": "subs2vec/deduplicate.py",103   "sha256": "1eac3739dbd0b976a41cf70945c6917b6b491d2b7e2dadf4b624ac2fda2da676",104   "language": "Python",105   "lines": 75,106   "truncated": false,107   "block": 10,108   "row": 12633109  },110  {111   "path": "subs2vec/download.py",112   "sha256": "8dfce443a1701fcf19a9edd5afb7db8fcd21818dff524fc88d604c9de364ec7b",113   "language": "Python",114   "lines": 59,115   "truncated": false,116   "block": 10,117   "row": 12292118  },119  {120   "path": "subs2vec/frequencies.py",121   "sha256": "fef223b651f277f51251698e2fdc52f3c6c83ac61d434fe83bfc580f6de52ae4",122   "language": "Python",123   "lines": 73,124   "truncated": false,125   "block": 10,126   "row": 13061127  },128  {129   "path": "subs2vec/lang_compile.py",130   "sha256": "64b62b9c0a982f2e5e8134950b7f4a7c2fa3caba71681686a5ad5fbcc254d784",131   "language": "Python",132   "lines": 46,133   "truncated": false,134   "block": 10,135   "row": 11597136  },137  {138   "path": "subs2vec/lang_evaluate.py",139   "sha256": "2fc5d426bb22ea43937a8153b473e6c0f40e2b55a2adc3682a80143844afa1b6",140   "language": "Python",141   "lines": 35,142   "truncated": false,143   "block": 10,144   "row": 11153145  },146  {147   "path": "subs2vec/lookup.py",148   "sha256": "288dce76102d9570cd46d6f2b95d6af6ae2e6b90c6cd17541d7199c0cab3efbe",149   "language": "Python",150   "lines": 27,151   "truncated": false,152   "block": 10,153   "row": 10894154  },155  {156   "path": "subs2vec/neighbors.py",157   "sha256": "e91824d5d8412fe5593f4c3e10a74f1b9f44709efb43c3b4cfab03cbf3565d9d",158   "language": "Python",159   "lines": 116,160   "truncated": false,161   "block": 10,162   "row": 13793163  },164  {165   "path": "subs2vec/norms.py",166   "sha256": "746ba502ea351f3d2380c13d9905111a49d1a4fa47d7042db7213dbd51ddec26",167   "language": "Python",168   "lines": 141,169   "truncated": false,170   "block": 10,171   "row": 14483172  },173  {174   "path": "subs2vec/paper_plots.py",175   "sha256": "e85ab08788aee83cb77733c87e915d8afe86726e5708504d4fb4168051797aec",176   "language": "Python",177   "lines": 246,178   "truncated": false,179   "block": 10,180   "row": 15622181  },182  {183   "path": "subs2vec/paper_stats.py",184   "sha256": "cb27528081a1df560991116b9a69c1ad3ad2371976c3bb020714a625b4374dfa",185   "language": "Python",186   "lines": 188,187   "truncated": false,188   "block": 10,189   "row": 15271190  },191  {192   "path": "subs2vec/paper_table.py",193   "sha256": "8a66d40b1a423a2e5d61ee1f73ca6e5e40b25c373ec4241d52b62b5eb245c560",194   "language": "Python",195   "lines": 68,196   "truncated": false,197   "block": 10,198   "row": 12384199  },200  {201   "path": "subs2vec/similarities.py",202   "sha256": "c06e2d76f0cdadff5f3223f41f7da7f731ec613ce3843af9ae908f93601748e8",203   "language": "Python",204   "lines": 123,205   "truncated": false,206   "block": 10,207   "row": 14197208  },209  {210   "path": "subs2vec/train_model.py",211   "sha256": "3dcce7d7d0022222fc65e2b89d2586a5583b3fd1c5bd014fdaa54c88dcb02c48",212   "language": "Python",213   "lines": 142,214   "truncated": false,215   "block": 10,216   "row": 14309217  },218  {219   "path": "subs2vec/utensils.py",220   "sha256": "8dccb5035ee4618e38116fa9293b9ad52da682a6f701f53acf6a81737a8c16b6",221   "language": "Python",222   "lines": 49,223   "truncated": false,224   "block": 10,225   "row": 11388226  },227  {228   "path": "subs2vec/vecs.py",229   "sha256": "8840e583938b54e01108f9edf4156b97d3896e55083c2e813ac38f523931c3eb",230   "language": "Python",231   "lines": 70,232   "truncated": false,233   "block": 10,234   "row": 12240235  }236 ]237}