Pre-release
This release is a pre-release and may not be stable for production use.
DeepSim
This toolkit provides deep learning-based similarity utilities.
Example
'''models for type
BERT:
shibing624/text2vec-base-chinese
sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
hfl/chinese-macbert-base:
uer/roberta-medium-wwm-chinese-cluecorpussmall
hfl/chinese-roberta-wwm-ext
Langboat/mengzi-bert-base
WMD:
w2v-light-tencent-chinese
'''
from deepsim import *
sim_utils=SimilarityUtils(type='w2v')
list_r=sim_utils.get_similarity('I like you!','I love you!')
print(list_r)
License
The deepsim project is provided by Donghua Chen.
1 maintainer
Metadata
1 maintainer
Release files for deepsim 0.0.1a0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| deepsim-0.0.1a0.tar.gz | 7.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| deepsim-0.0.1a0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 12.7 kB
Release files / deepsim-0.0.1a0.tar.gz
| Download URL | deepsim-0.0.1a0.tar.gz |
|---|---|
| Size | 7.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/4.0.1 CPython/3.9.13
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Release files / deepsim-0.0.1a0-py3-none-any.whl
| Download URL | deepsim-0.0.1a0-py3-none-any.whl |
|---|---|
| Size | 5.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.13
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