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数据集:

biglam/berlin_state_library_ocr

任务:

填充掩码 文本生成

子任务:

masked-language-modeling language-modeling

语言:

de nl en

计算机处理:

multilingual

大小:

1M<n<10M

语言创建人:

expert-generated

批注创建人:

machine-generated

其他:

ocr library

许可:

cc-by-4.0
数据集介绍 文件清单
文件路径: biglam/berlin_state_library_ocr / data
train-00000-of-00053-54c67aaf0fee067a.parquet
174.37 MB
2022-08-04 20:16:10
train-00001-of-00053-c5dc8909088e9468.parquet
192.99 MB
2022-08-04 20:16:43
train-00002-of-00053-9f83b67cf6f0ce8f.parquet
177.31 MB
2022-08-04 20:17:14
train-00003-of-00053-1c021c812cff7dd0.parquet
191.81 MB
2022-08-04 20:17:48
train-00004-of-00053-0d1ecfb1347af5b7.parquet
197.47 MB
2022-08-04 20:18:22
train-00005-of-00053-4168aa599c53ee7d.parquet
185.52 MB
2022-08-04 20:18:56
train-00006-of-00053-50084c937fae8de4.parquet
193.51 MB
2022-08-04 20:19:30
train-00007-of-00053-910452241f1cc000.parquet
178.25 MB
2022-08-04 20:20:02
train-00008-of-00053-899228f3bfff11a2.parquet
192.81 MB
2022-08-04 20:20:43
train-00009-of-00053-1d777841649ed3e5.parquet
182.8 MB
2022-08-04 20:21:16
train-00010-of-00053-582a1e080134cb45.parquet
176.2 MB
2022-08-04 20:21:51
train-00011-of-00053-9d77d6f134aefea0.parquet
189.89 MB
2022-08-04 20:22:26
train-00012-of-00053-deb45d1dad3e9633.parquet
179.84 MB
2022-08-04 20:23:39
train-00013-of-00053-9f30939b75df9c81.parquet
167.75 MB
2022-08-04 20:24:19
train-00014-of-00053-dcf0ebf39a1d56ec.parquet
192.7 MB
2022-08-04 20:24:54
train-00015-of-00053-f66905050b0e932f.parquet
174.19 MB
2022-08-04 20:25:34
train-00016-of-00053-27344d08aa924504.parquet
192.84 MB
2022-08-04 20:26:08
train-00017-of-00053-013a08b07a2b6431.parquet
186.3 MB
2022-08-04 20:26:42
train-00018-of-00053-1fe73cba9389c848.parquet
185.27 MB
2022-08-04 20:27:18
train-00019-of-00053-90d3a76c7c20c26d.parquet
183.25 MB
2022-08-04 20:27:53
train-00020-of-00053-ece1d3312093ad5f.parquet
186.3 MB
2022-08-04 20:28:23
train-00021-of-00053-df8189ea7b114389.parquet
184.92 MB
2022-08-04 20:29:08
train-00022-of-00053-b5974836f2650f78.parquet
176.31 MB
2022-08-04 20:29:54
train-00023-of-00053-29bb6e14bb57e8ab.parquet
201.11 MB
2022-08-04 20:30:34
train-00024-of-00053-bb7bfb81c5cd4ef4.parquet
165.28 MB
2022-08-04 20:31:06
train-00025-of-00053-2831a1738fe2904c.parquet
186.81 MB
2022-08-04 20:31:40
train-00026-of-00053-3e97a96c74a580e6.parquet
171.11 MB
2022-08-04 20:32:15
train-00027-of-00053-e735257bdb877123.parquet
179.02 MB
2022-08-04 20:32:49
train-00028-of-00053-b69d79095aa1bb23.parquet
179.16 MB
2022-08-04 20:33:23
train-00029-of-00053-7562599829ea5f30.parquet
195.13 MB
2022-08-04 20:33:58
train-00030-of-00053-433c28482dca0376.parquet
186.23 MB
2022-08-04 20:34:32
train-00031-of-00053-492a0a3f3421299f.parquet
187.94 MB
2022-08-04 20:35:05
train-00032-of-00053-71405ad23e7910b0.parquet
187.46 MB
2022-08-04 20:35:48
train-00033-of-00053-2bcb3b609c15ffca.parquet
181.67 MB
2022-08-04 20:36:22
train-00034-of-00053-ecdd548be634d9c8.parquet
172.77 MB
2022-08-04 20:37:53
train-00035-of-00053-515807769c15af12.parquet
177.48 MB
2022-08-04 20:38:27
train-00036-of-00053-9cab591076b49f5e.parquet
178.17 MB
2022-08-04 20:39:05
train-00037-of-00053-a42d114ccccb89c4.parquet
177.94 MB
2022-08-04 20:39:37
train-00038-of-00053-08a5636e3ae46b8c.parquet
188.55 MB
2022-08-04 20:40:12
train-00039-of-00053-c206835b2ca77d3b.parquet
185.18 MB
2022-08-04 20:40:46
train-00040-of-00053-ea090235ccf2d440.parquet
203 MB
2022-08-04 20:41:23
train-00041-of-00053-bd5025914bc36fec.parquet
170.27 MB
2022-08-04 20:41:54
train-00042-of-00053-cd6b6966784e181c.parquet
182.68 MB
2022-08-04 20:42:28
train-00043-of-00053-b1fc98fc7d55b5e2.parquet
174.36 MB
2022-08-04 20:43:01
train-00044-of-00053-fd127ba53dc2563d.parquet
181.89 MB
2022-08-04 20:43:34
train-00045-of-00053-12aea9ea4bae6973.parquet
186.21 MB
2022-08-04 20:44:08
train-00046-of-00053-4188df445e745373.parquet
173.64 MB
2022-08-04 20:44:42
train-00047-of-00053-7a0b0b9df2617903.parquet
185.88 MB
2022-08-04 20:45:15
train-00048-of-00053-834c288c28811ce5.parquet
174.59 MB
2022-08-04 20:45:51
train-00049-of-00053-a3c2d70c2ca5c79f.parquet
176.09 MB
2022-08-04 20:46:24

作者:

biglam

数据集大小:

8.94 GB

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