Wheelodex » Projects » texi

texi

View on PyPI — Reverse Dependencies (0)

0.2.3 texi-0.2.3-py3-none-any.whl

Wheel Details

Project: texi
Version: 0.2.3
Filename: texi-0.2.3-py3-none-any.whl
Download: [link]
Size: 72333
MD5: 2d703a1279a4462fb122aa2dde22e4a7
SHA256: 832840d087da419a28cac4be8b08efb5beed2b06a07265643f606c78d7338da6
Uploaded: 2022-05-24 06:48:22 +0000

dist-info

METADATA · WHEEL · RECORD

METADATA

Metadata-Version: 2.1
Name: texi
Version: 0.2.3
Summary: Text processing toolbox.
Author: Yevgnen Koh
Author-Email: wherejoystarts[at]gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.8,<4.0
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: plotly
Requires-Dist: pyahocorasick
Requires-Dist: pycarton
Requires-Dist: pytorch-crf
Requires-Dist: pytorch-ignite
Requires-Dist: torch
Requires-Dist: transformers
[No description]

WHEEL

Wheel-Version: 1.0
Generator: poetry 1.0.8
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
texi/__init__.py sha256=lbp1CkswYjAMQKLmz01DhveSc9qIqKE7LhXzYwt9bng 185
texi/apps/__init__.py sha256=HvcQDe9GyP3SdT0Y19nqFiS8MPnbgk6nsNT0w0MlP-M 93
texi/apps/classification/__init__.py sha256=6nd-HwXOowc8LLRyM67Rid5YOiybrEmo3NI6ff6d8ak 52
texi/apps/classification/train.py sha256=ibEiUDLrCi7eUfQTmKLRS-7HxJPmRAJ5XurDviJ8Y8c 5622
texi/apps/ner/__init__.py sha256=u8VXWtlMXOPo3km2y05e64B5PKgaXVdeo6kOHQ2uqXk 1424
texi/apps/ner/conlleval.pl sha256=nliYN4JmVny6VMEW4ojhnhx82OBkcY0QAN1XFa3YbcI 12685
texi/apps/ner/data.py sha256=W7nvc_6yzvBca3r9-iXeClaKFGNM6xzXmDW4cnf5CTs 10641
texi/apps/ner/eval.py sha256=1aMW2N8MnHkzUxD7GJtDw-9xfaxazWp5ZixScnTwU90 3740
texi/apps/ner/span_utils.py sha256=cAgfXyyr82WZjbDE4gd580mg4TseNg3eIlesQRX6qJM 2989
texi/apps/ner/templates/entity_examples.html sha256=6_Tz325NJDqj6gtEyfgqb6c7ytbiNB8D04bmGhDbHVs 7706
texi/apps/ner/templates/relation_examples.html sha256=0QS-Kdbm4oplFC5Lb7CAo97LbVqUXf0YP43NLEchQ9Q 8259
texi/apps/ner/utils.py sha256=v0cvhfLOdjRs5N5t0Pi-r0_Y7KDJbN0aCbjvUV-_F7o 20333
texi/apps/ner/visualization.py sha256=_EfycBrJLjM9ZucT-Xc1ZQmq23D9xOYMowsgQhWafBE 6388
texi/apps/text_matching/__init__.py sha256=6nd-HwXOowc8LLRyM67Rid5YOiybrEmo3NI6ff6d8ak 52
texi/apps/text_matching/train.py sha256=Z8TKhBXvOamj0k_Na82N7Cm6wJaksexwHYUXP8kMjgg 5919
texi/datasets/__init__.py sha256=_9yICft73VwZzbhfvRXAw1orWuehAyXUt9CkE-Qiapc 1387
texi/datasets/classification.py sha256=RdlDafWi-gI8lwFx1RbU4iYygYGBfun6fyQAk4vX298 11601
texi/datasets/dataset.py sha256=mIdsqDgkoz6t-eAccz1KHT7zvgE6XtXcBOqv6EIjNLc 10419
texi/datasets/question_answering.py sha256=4P_4VBzp4jexykjjJrai2rOmKfCLdDSwdCI4EYkQ19w 528
texi/datasets/text.py sha256=KOmYgz_LevUJPQpfN16oC8Hro8-BYFk8nH7o_dSg9xk 1664
texi/datasets/translation.py sha256=qq_lLt7g4YQAvNv_zxg2MrBwP_aq7ioJwcAATzxDuRg 356
texi/embedding.py sha256=vn06PqkHuPLwEqk7NqyUIstrwRyWoNxf_wNIOXuDPiQ 1386
texi/metrics.py sha256=0MTVS5QvnQM34sbX6qvaEVlbwMvEQdwcuXt3J6k188U 5404
texi/preprocessing.py sha256=-t6Dd3CFOea6-y1zf3i4xvMa1CUbXM5BAgvOFKEnVhY 4030
texi/py.typed sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
texi/pytorch/__init__.py sha256=uks46tP0SkxU1UbnKuc67m4nY03y7_UDgzlyu4X4rUM 83
texi/pytorch/dataset/__init__.py sha256=j6A_rhZVCPaJamQIlLo7pNq5cKMULaEOqrq-5Vpr6xo 355
texi/pytorch/dataset/collator.py sha256=WavdJjFsicou8DcIm8nZCvNNG18tPy2iP-7TX6I82h8 3853
texi/pytorch/dataset/plm_collator.py sha256=KtOtXXpXLbMOvtCUpSk-PpPBiskNugTb0JRkwJPLnJI 6240
texi/pytorch/metrics/__init__.py sha256=akrRs1XJBjhE4Gx1esd2tXJ-QBTA4RRbs1Urq3MTbvg 901
texi/pytorch/metrics/general_accuracy.py sha256=DaAfLICSsBQxwvsgDEshm5fW8Z7UQ-VpZlrZ8qLbdPo 1710
texi/pytorch/metrics/mean_reciprocal_rank.py sha256=rogj7jp6zByHpjcp9Y8eb-aS2xCWSvV7vTfitFM79Zs 1388
texi/pytorch/metrics/metrics.py sha256=H6szPo2vCSemi73DfCrgsW0p2WIHJOomnpdovfzHGbU 2022
texi/pytorch/metrics/ner_metrics.py sha256=NLi1zkVIb8ijrCmc7qYF6XLZoOn883YG802QatgNTz8 4054
texi/pytorch/metrics/re_metrics.py sha256=mGc34Q81TQhE7Qmu-Vq9PAVIn6uIUgoSADHSBKO8Hzg 5697
texi/pytorch/metrics/sequence_labeling_metrics.py sha256=wQtCTycatZobgZxRx1scAey11uiW-TOFfNz5WSU2TrM 1925
texi/pytorch/models/__init__.py sha256=aMOwe4V7P4w65SnuP5eeH9y0iGXyWcBCxxS5301k0xM 865
texi/pytorch/models/classification.py sha256=smcAsk_YfaP6a1YamEOq3CZ_hYCcwQMfm-O7fbFRUZ0 3641
texi/pytorch/models/question_answering.py sha256=N3TJAeLGES6K-QUUVz2Bp7lX1QGIHM64KqjD-3uXtXs 740
texi/pytorch/models/sequence_labeling.py sha256=tfcy6S4R3KSBWdQMTPFVuyvuu6NdAIRL3Wds4G5Lvio 9965
texi/pytorch/models/spert/__init__.py sha256=NiX8QE6mGEJ90x2KpIRKkVUMORgPOkYkCAtAYiMqIRI 777
texi/pytorch/models/spert/dataset.py sha256=OILS4pPMFpgiDudx-KIScEq7dLo4O7tc51B7gStyWtE 10134
texi/pytorch/models/spert/loss.py sha256=m0KCAqd069hQzssgVhNiuCLpVti4UpElgWChJPhDn8Y 2176
texi/pytorch/models/spert/model.py sha256=ssGGozNjOmToaLeimh99wiWlfJhgT7E1fqnTQqVpM9s 11346
texi/pytorch/models/spert/prediction.py sha256=mBWRUFRwVKMURyNl18iYxgzvFKbJevZGoudQfWK9VHY 7037
texi/pytorch/models/spert/sampler.py sha256=TihBPMy_VdIp4oJQE_4yfncgvHoWRntW7OoQXaqOXWk 140
texi/pytorch/models/spert/training.py sha256=aqasAOMy2kYEBNdxflnQc9jvGbnntnnwDz8X21hDY7s 13712
texi/pytorch/models/text_matching.py sha256=5LfZ7YXmd65RZuzw-_0NHrnbB7_vfC4Hgtmh_uK89wg 14803
texi/tagger/__init__.py sha256=JhrWGoigGUz38DQA-rvBbrcoSGnMM-p-fFZbLj41q-M 381
texi/tagger/sequence_labeling.py sha256=dpFufdlr6Wifk7wFeQTyBiCwqfG7K3BJhG0gRLlWYDw 7591
texi/vocab.py sha256=_nHw2bunlQ_paOhedLUwUCzsLDrNXf2WiN9P7Ha5p0o 5902
texi-0.2.3.dist-info/WHEEL sha256=DA86_h4QwwzGeRoz62o1svYt5kGEXpoUTuTtwzoTb30 83
texi-0.2.3.dist-info/METADATA sha256=tMDYclZB4Yo-CtcZqWzM-8NQaV16w_q_c5wqLXe4YjE 592
texi-0.2.3.dist-info/RECORD — —