vecto/__init__.py,sha256=kr4SEH6ue1zgpbJ92aSEESbio5OY0jxi2iCrQrw8VoI,259
vecto/__main__.py,sha256=jKaebOiB2SKpIYKXyS01YKsvAIF5MLSMVFqLsMwdkIU,59
vecto/_version.py,sha256=zynzBXZVmO1q1u3fAC2CNq5jH5hy4qxIvGwRsbdTSZ0,51
vecto/cli.py,sha256=SmrbS3IYwgMtubZq61PXjRruv42AaHnPy2UAP3X6UaY,1215
vecto/config.py,sha256=UaHBi-9kMFlCQAOAyL9IL05CTz03gHsTdzFMdayNhMc,587
vecto/benchmarks/__init__.py,sha256=dR2XoMZ4udevf41XWuth2Ks-8AGMFlbdyUirCQZgJuA,3789
vecto/benchmarks/base.py,sha256=DaJXb2k8cq1ypFZg4OHYv3iCNbFWddEkbooDqHyul5A,268
vecto/benchmarks/visualize.py,sha256=OjEkuQaJkwGY_CTxNyra_EQIScmjZLFQBCD_FEWcuVw,3935
vecto/benchmarks/analogy/__init__.py,sha256=KBXKqxBEuCVB5-t7WB0Bv6c_kAEapp3mok5rPVGV__w,910
vecto/benchmarks/analogy/analogy.py,sha256=eGfieGNdWnKkzy6zxidpTEWuV6f8G_dgal7X2cKTlBQ,9357
vecto/benchmarks/analogy/io.py,sha256=b8QVSR-07S0ZAiCSoT3XdR2nEL0gOt3irWBcPx8k5Tk,911
vecto/benchmarks/analogy/solvers.py,sha256=bi-JUVd2jyqBlWCVxBcy26fP9B_QTxDJifUwARTjhDM,14837
vecto/benchmarks/categorization/__init__.py,sha256=IvchtkLS8ymsUhVW5niyq7IZLBV9aP2B1ZcIE6eic3c,1763
vecto/benchmarks/categorization/categorization.py,sha256=HnS4rytNXGqLOq7GL1jNuLgCoBDWMZwvDtjdbBuz91Q,8758
vecto/benchmarks/categorization/metrics.py,sha256=ZAnNLVDLCuf0llimwswmbZdu22B6LdXU1pfiL6VUywI,846
vecto/benchmarks/language_modeling/__init__.py,sha256=dELR1yTaVKH3gWFv4aapgbc_2tLDzKKdOu4m37Kb_Fc,1039
vecto/benchmarks/language_modeling/language_modeling.py,sha256=ByBN8Jf4CWIBkZalV4iEk8ix9Jrf4238IxA0EHLWN4M,13637
vecto/benchmarks/outliers/__init__.py,sha256=HwE2Vy-5EqPycDbmOjYzlfNPDC8fzeyLK7lPgRhCpfw,23
vecto/benchmarks/outliers/__main__.py,sha256=TYYA3RM0MlbZXwR8O2thg2pHQux0uPiXw7TEY-obcJM,1458
vecto/benchmarks/outliers/outliers.py,sha256=3qjbjE4sCc8zF-_-nDJDkEImRlV_qJ4q3eYT_r3cPOc,6261
vecto/benchmarks/relation_extraction/__init__.py,sha256=4uJZPUY3u8QNNrzUGxzRa9223050m_9_UcNHCRDNj8U,886
vecto/benchmarks/relation_extraction/preprocess.py,sha256=l6oVjIosEn3Z_DqkmCoQpCWdsg3jLKoKY5RYBuB-gH0,4460
vecto/benchmarks/relation_extraction/relation_extraction.py,sha256=0yop_qaGrEr9B6c8Ai4BHc_7qGZfKEQQZ4lQpk-_Av4,5636
vecto/benchmarks/sequence_labeling/__init__.py,sha256=H68eNXhzcBWmuGnVtOWEICfldlKTmA4jLPUgOrEu9XM,427
vecto/benchmarks/sequence_labeling/sequence_labeling.py,sha256=7NpogAz5vIpmVNPr8IouHp0FpHlO4bMeiVMdgh3wWGY,9078
vecto/benchmarks/similarity/__init__.py,sha256=hJX0Pnipo0pFSLaZiPAJUP4J8Pe7qubK69kB213Zrlw,309
vecto/benchmarks/similarity/similarity.py,sha256=itOK-Wo1LZwCczU64pkCtj1XKz2FLmne47Gcjj4EBEk,5877
vecto/benchmarks/synonymy_detection/__init__.py,sha256=iYEiu-KYyzb9_OcgbGnULld5ZUaOXTJ1nk54CN8aTnQ,33
vecto/benchmarks/synonymy_detection/__main__.py,sha256=ma1qMxtWXp9_BziqI8NfISQKSTZpkaR5b5BUE6n9Usk,1448
vecto/benchmarks/synonymy_detection/synonymy_detection.py,sha256=18BKCI3n8RTeumwTNsnuL2F3N_jKCZUwd8PUf3vx3YY,4780
vecto/benchmarks/text_classification/__init__.py,sha256=cgvHRpyLcPPA4b1vz3_sTwAvZYIF5Gzz6xieiXaISIo,1774
vecto/benchmarks/text_classification/nets.py,sha256=pE5ElibGqkqBE3HBynprC8JCFrQmKQcvMoAs_GvhWdA,10037
vecto/benchmarks/text_classification/nlp_utils.py,sha256=f3keJ0Wl8ZGkVEnTusLbR6AGIvIL3MkDXgw-uAXXse0,2279
vecto/benchmarks/text_classification/text_classification.py,sha256=do6pcffj3lOl9wVDXFOXm6OyG6ZF71rFeYPpJ4yo3y8,10104
vecto/benchmarks/text_classification/text_datasets.py,sha256=D0hTLcPTgZuWA7kRLHJQHHQGDWxoUMDoFoydvvjKybc,5925
vecto/corpus/__init__.py,sha256=N2rWAI4Oydd1iVlszDx6Cdd06cC74oGXMTVcJxSKdKE,234
vecto/corpus/base.py,sha256=cdAaDg4rl429LSRMnKNb9-25Wm98v3B-tiSZifdjgoo,928
vecto/corpus/corpus.py,sha256=wuLTKmKdbsEaRXgjqEv8wMMASIXbq_gFj4i7ZIC_1lE,5144
vecto/corpus/iterators.py,sha256=aWE5-enUQHXn5PxE4vrHUFmqzHEoYKVujPkE_Zdy7tM,7727
vecto/corpus/tokenization.py,sha256=LyW5uSqTQf6VsmtwV3Zd1jdfi6NiyBd9TQ7m_Zkl9-E,4605
vecto/data/__init__.py,sha256=bRgg1QP0rebs1hdC7DrD6HVFHM6HgMgwb6SkX5qfzXg,47
vecto/data/base.py,sha256=hWAQF74pW9-m-cbOtfpOL1j8ju-2cYKYt4iJ9X_qXls,5061
vecto/data/io.py,sha256=0zakf-WqUqbFB68lEboDDYuxMj0d8MJVt0KfAZnYTcs,1913
vecto/embeddings/__init__.py,sha256=SuyUB2iagapeJAqRQVk6Stbf4ONoQK_iR_EOhcFthzQ,3541
vecto/embeddings/base.py,sha256=E2p3zzIEDe10_SwKnmWkGn5ofT63b8X6h3IIVEDeST8,221
vecto/embeddings/dense.py,sha256=XFMrFUKtrR43mI1Q2Z7rEUmroQae3hJv5pG7NMN4Mns,9467
vecto/embeddings/legacy_w2v.py,sha256=YXvhwfD-K8tDlrS8cGhU6MYSI5YekdJAFFBAaEYSnkM,1645
vecto/embeddings/train_word2vec.py,sha256=tSlIAN38p96k3SRPqbXUWiuwr5zDGJdPBFqbpKpBVbY,11728
vecto/embeddings/utils/__init__.py,sha256=eIupgUayc6Y5Gb5vxq-Vnzm7p4ZwKi--dHp05681X_o,40
vecto/embeddings/utils/subword.py,sha256=8k3CtZ_52ZsGyWkS6FfOjZ0c22x0aqf2LQG2OoGc2Wg,24326
vecto/embeddings/utils/word.py,sha256=gmgFElcD1cmo2lFpLpPvbV9Ijjx3slX3dNabLXKAwWM,5969
vecto/utils/__init__.py,sha256=J02asyykag_gX84zUcxG70U4tCghQTCHTEXUoUeYdC8,243
vecto/utils/blas.py,sha256=b6d-lVqAH5qsqrDkEsuWFx2Zaawu7vWCqWAPm3_XX2k,232
vecto/utils/convert.py,sha256=NETJGdafVdxnwsuscv1cmwXE27yWXTUWXW2WEC6zzNU,364
vecto/utils/data.py,sha256=E3G0Xwny5q6iz3atnirEHltBdCWlhsymaRhjEpyHgFc,1195
vecto/utils/fetch_benchmarks.py,sha256=pvZR7MBntMILEAv-tPq7yEIuN_HetXRwgcttq_X_91c,435
vecto/utils/formathelper.py,sha256=uecUXotILG6fNrVyPKdJ00Fg4ewuFkAoAAbq_DFFteU,691
vecto/utils/metadata.py,sha256=kdIdfKx_lgLp8yUQtqhTe2aUZk11OktRE6xEfEPlf0U,2175
vecto/utils/tqdm_utils.py,sha256=RUyFLO39OwY0hlODVwUmfrIEvVmVFJUa9tGj7-hN3gw,263
vecto/vocabulary/__init__.py,sha256=0DKouQT-7Qn9umx6ZXUrOWvF_iXB7Hofu1tMVXjgWlE,301
vecto/vocabulary/__main__.py,sha256=f8X_HqSadaH8ZCi5GfaICqzfEsWN_j3_9vrOkh3pFtk,2015
vecto/vocabulary/vocabulary.py,sha256=EyIK7wTik4hyqZJvCoi2llk5Eqxe37InUmjuegtvNiM,11718
vecto-0.2.8.dist-info/LICENSE,sha256=HyVuytGSiAUQ6ErWBHTqt1iSGHhLmlC8fO7jTCuR8dU,16725
vecto-0.2.8.dist-info/METADATA,sha256=ihwEKXV_H1Oe-sXUelmoyp4nlHe1UprvJI9h5CLNgvE,3304
vecto-0.2.8.dist-info/WHEEL,sha256=g4nMs7d-Xl9-xC9XovUrsDHGXt-FT0E17Yqo92DEfvY,92
vecto-0.2.8.dist-info/top_level.txt,sha256=JTxR-TXV4w4ndYdfn_UTAyPKX82qktDXQk9ouhKhGhY,6
vecto-0.2.8.dist-info/RECORD,,
