Wheelodex » Projects » bert-for-sequence-classification

bert-for-sequence-classification

View on PyPI — Reverse Dependencies (0)

0.1.1 bert_for_sequence_classification-0.1.1-py3-none-any.whl

Wheel Details

Project: bert-for-sequence-classification
Version: 0.1.1
Filename: bert_for_sequence_classification-0.1.1-py3-none-any.whl
Download: [link]
Size: 17361
MD5: 337229c23ad7ad0dced11aa3fc71d21b
SHA256: 9931feb38746ac4132ee8ccd17c448f83de42534d9ef575c3c5eb03d43cc9d01
Uploaded: 2023-07-21 14:50:08 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: bert-for-sequence-classification
Version: 0.1.1
Summary: Easy fine-tuning for BERT models
Author: Tatiana Iazykova
Author-Email: tania_yazykova[at]bk.ru
Keywords: python,bert,deep learning,nlp
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: transformers (>=4.21.0)
Requires-Dist: torch (>=1.7.1)
Requires-Dist: numpy (>=1.19.5)
Requires-Dist: pandas (>=1.1.5)
Requires-Dist: scikit-learn (>=1.0)
Requires-Dist: pyyaml (>=6.0)
Requires-Dist: openpyxl (>=3.0.9)
Requires-Dist: wget
Requires-Dist: tqdm
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 2566 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.40.0)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
bert_clf/__init__.py sha256=DUrKVNFR6oKky1rUAUkeSM6xg8RkylAUDU8LIju6lgo 457
bert_clf/pipeline.py sha256=itFfpTHNrPhl0gyHpHNpDAXbhIqsmqHoVLSX9YCgiF4 2895
bert_clf/utils.py sha256=ovyiiSiWLR5RTrLMVSl_lRiUkxJNPpV-w0xGCWF_ssU 1354
bert_clf/src/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
bert_clf/src/dataset.py sha256=eAlFXZfhjOUB4YvJvog6pU5wM4Wk_5bVnuqDXdik-8Y 1154
bert_clf/src/early_stopping.py sha256=FSj8SBeY0LgrZA_e3MjoJS0vCACOlClG4u61F13czX8 999
bert_clf/src/preparing_data_utils.py sha256=JETaT9TwRJoprJzbGAaetMlQ63b_KwE92vkEadlkIcA 4717
bert_clf/src/training_utils.py sha256=gwF7DzurhwfoE1TB3PWSLCtxsvWALMddmAFkwp1_fjs 7868
bert_clf/src/core/BaseDataset.py sha256=DQJcmPqIsvZH93_5gVqV8oydD3siHR3-TkmyDI07wFc 1952
bert_clf/src/core/BaseModel.py sha256=a_b9esGR7h4bf7amnkgjuQIVPQioz5J4Zd3Q4zgXS2A 1943
bert_clf/src/core/Fabric.py sha256=adqR57ISSEXGUkob5YPcOxLQisG-qZSA7ueztf0KqS4 903
bert_clf/src/core/__init__.py sha256=cZThrJs1Ubj6IGCUA-pYUp_4Z2ijgxL-g0MLKrYHvsE 164
bert_clf/src/core/utils.py sha256=RAwTIygrEMUYFd5RygEoNLS_zbgDIM-BbBeJlRLke1A 301
bert_clf/src/models/BertCLF.py sha256=Dw36GKC6xbMJtrF7piG4neHbx2JC0Zj59XvFFdyyZHE 1806
bert_clf/src/models/EncoderCLF.py sha256=eRON0QIeV_Ho4UceA4nmsvDxmPdBq5fhWLMWlVEwJTc 3059
bert_clf/src/models/__init__.py sha256=qTTOaBXQ0ha4wE4jigBydRruc0C3I6lXM55wos0P5bA 112
bert_clf/src/pandas_dataset/PandasDataset.py sha256=PITMCA0tbbTWNq1s52n8jh5AKJiXbCnTebU-C4MchwY 2798
bert_clf/src/pandas_dataset/SimpleDataFrame.py sha256=PfJSMi0LZk1fl8CaN-MMgY6WWbWu20hLwV_46AQm80o 1884
bert_clf/src/pandas_dataset/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
bert_for_sequence_classification-0.1.1.dist-info/LICENSE sha256=fWMroOqbYhaGhN-UUs4_5VJwlJ9Qc54w08zHtVpEhSU 1073
bert_for_sequence_classification-0.1.1.dist-info/METADATA sha256=wL_e7OJDidEHm7uaNTlpnW4_fprrm3UUqLgaI67y6YU 3315
bert_for_sequence_classification-0.1.1.dist-info/WHEEL sha256=pkctZYzUS4AYVn6dJ-7367OJZivF2e8RA9b_ZBjif18 92
bert_for_sequence_classification-0.1.1.dist-info/entry_points.txt sha256=MmsZg8BWm21pH_osViylfiyAw8R1A2Xl_4t9O4LjKJU 58
bert_for_sequence_classification-0.1.1.dist-info/top_level.txt sha256=R8RXHIwK7ymxLrfcwXt97yE2Soy23sx2i7ceKfx6cM8 9
bert_for_sequence_classification-0.1.1.dist-info/RECORD — —

top_level.txt

bert_clf

entry_points.txt

[console_scripts]
bert-clf-train = bert_clf.pipeline:main