TextVectorizer
A Library for representation learning of Text using Transformers such as BERT, AlBERT, RoBERTA and spacy
Text Annotation
from TextVectorizer import Vectorizer from TextVectorizer import Vectorizer vec = Vectorizer('bert') for i in vec.annotate('Hi I am Rahul'): ... print(i.text,i.pos_) Hi INTJ I PRON am AUX Rahul PROPN
Document Similarity
from TextVectorizer import Vectorizer vec = Vectorizer() doc1 = 'Apple is a company' doc2 = 'Apple is fruit' vec.similarity(doc1,doc2) 0.622238214831199
1 maintainer
Metadata
1 maintainer
Release files for TextVectorizer 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| TextVectorizer-0.1.0.tar.gz | 3.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| TextVectorizer-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.7 kB
Release files / TextVectorizer-0.1.0.tar.gz
| Download URL | TextVectorizer-0.1.0.tar.gz |
|---|---|
| Size | 3.1 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.48.0 CPython/3.7.3
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Release files / TextVectorizer-0.1.0-py3-none-any.whl
| Download URL | TextVectorizer-0.1.0-py3-none-any.whl |
|---|---|
| Size | 4.6 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.48.0 CPython/3.7.3
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