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0.242 vembed-0.242-py3-none-any.whl

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Project: vembed
Version: 0.242
Filename: vembed-0.242-py3-none-any.whl
Download: [link]
Size: 9813
MD5: 1c8c16712796edffdc8db723db2ec5b9
SHA256: a2e67625606768f2cf147e008de5a1ff5c2c398d3b87adcefe997980dc4d7c49
Uploaded: 2023-11-22 09:00:21 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: vembed
Version: 0.242
Summary: Package providing methods to create Vector Embeddings from Strings, calculate similarities between lists of Strings, and Generate Visualizations such as Heatmaps from simple Lists.
Author: kuro337
Home-Page: https://github.com/kuro337/vembed
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.5
Requires-Dist: sentence-transformers
Requires-Dist: torch
Requires-Dist: transformers
Requires-Dist: pandas
Requires-Dist: matplotlib
Requires-Dist: seaborn
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 10069 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.41.3)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
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vembed/model/transformer_model.py sha256=qC9T1d3jllLOkrao2e7ZCKdhmyYtQHLa_SEvcAmVmtA 1487
vembed/similarity/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
vembed/similarity/get_similarity.py sha256=MBV0vXtxVWp0avKYz01T7eEGsta0j1JzBRtuXBaGgVU 4249
vembed/string_to_vector/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
vembed/string_to_vector/mpnet_paraphrase.py sha256=YprCUk0in1FMVCUAfWEVjr9iFTpzHOIFpI1p88L061Y 5125
vembed-0.242.dist-info/LICENSE sha256=Njd5AfOdsBFKb7_kwel9RH9gNSD74SC5lADGDhbn40U 1064
vembed-0.242.dist-info/METADATA sha256=eazsNGjX0eru2Z9TaWlJJw_iwbQ2AAT2eJVdihtfOJA 10759
vembed-0.242.dist-info/WHEEL sha256=Xo9-1PvkuimrydujYJAjF7pCkriuXBpUPEjma1nZyJ0 92
vembed-0.242.dist-info/top_level.txt sha256=LvW49s_tmqlqre80N42ApFXJWEV9cCVT0MeeK77GYWg 7
vembed-0.242.dist-info/RECORD — —

top_level.txt

vembed