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0.8.1 concise_concepts-0.8.1-py3-none-any.whl

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Project: concise-concepts
Version: 0.8.1
Filename: concise_concepts-0.8.1-py3-none-any.whl
Download: [link]
Size: 15607
MD5: 27e848f17b0d89d3bbf7e39bcfe83706
SHA256: 42fa5704b44c278da70258f689d92305e07cf4a40d0f7c7c54891eaac0d729bc
Uploaded: 2023-06-19 13:01:23 +0000

dist-info

METADATA · WHEEL · RECORD · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: concise-concepts
Version: 0.8.1
Summary: This repository contains an easy and intuitive approach to few-shot NER using most similar expansion over spaCy embeddings. Now with entity confidence scores!
Author: David Berenstein
Author-Email: david.m.berenstein[at]gmail.com
Home-Page: https://github.com/pandora-intelligence/concise-concepts
Project-Url: Documentation, https://github.com/pandora-intelligence/concise-concepts
Project-Url: Repository, https://github.com/pandora-intelligence/concise-concepts
License: MIT
Keywords: spacy,NER,few-shot classification,nlu
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Requires-Python: >=3.8,<3.12
Requires-Dist: gensim (<5,>=4)
Requires-Dist: scipy (<2.0,>=1.7)
Requires-Dist: sense2vec (<3.0.0,>=2.0.1)
Requires-Dist: spacy (<4,>=3)
Requires-Dist: spaczz (<0.6.0,>=0.5.4)
Description-Content-Type: text/markdown
[Description omitted; length: 8002 characters]

WHEEL

Wheel-Version: 1.0
Generator: poetry-core 1.2.0
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

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concise_concepts/conceptualizer/Conceptualizer.py sha256=pmrBxYJIKrKkyHkLCpisMT_xQnvFgQSFyolBE3vVPLs 25645
concise_concepts/conceptualizer/__init__.py sha256=wcLwIpwsv-R2w8_FimGkSFBc5oDoldTJsDkYUS2T-t0 97
concise_concepts/examples/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
concise_concepts/examples/data.py sha256=xn51xkWoMk6F3WgMZufeKRDmha3zwMs4yqxaqAmP6V4 759
concise_concepts/examples/example_gensim_custom_model.py sha256=oZzfBidQ_JQhJZBRkZTgbZdyss5YZM7Uxhsyuw1Km4E 862
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concise_concepts/examples/example_gensim_default.py sha256=YVxQ-PX6yeqhswA3RlmQVzqwUJ9Su93QQRm_MMwvlBk 316
concise_concepts/examples/example_spacy.py sha256=CNji5ostkK9zdvEXAzyEPcSimhrgPSUJPEg2QBE2zF0 268
concise_concepts-0.8.1.dist-info/entry_points.txt sha256=kWR5lBpEza-_9Lb4nG4bnClddDrd_b1ZugSZho1Qs6I 73
concise_concepts-0.8.1.dist-info/LICENSE sha256=N0EVGHdOYZ7YEJVUCllwq0kJp4buqN-AC_W3FYfktNg 1077
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concise_concepts-0.8.1.dist-info/RECORD — —

entry_points.txt

[spacy_factories]
spacy = concise_concepts.__init__:make_concise_concepts