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Home / zh_core_web_sm-3.8.0
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zh_core_web_sm-3.8.0-py3-none-any.whl 2024-09-29 48.5 MB
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zh_core_web_sm-3.8.0.tar.gz 2024-09-29 48.6 MB
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README.md 2024-09-25 3.3 kB
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zh_core_web_sm-3.8.0 source code.tar.gz 2024-09-25 6.0 MB
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zh_core_web_sm-3.8.0 source code.zip 2024-09-25 7.5 MB
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Totals: 5 Items   110.6 MB 9

Downloads Downloads (wheel)

Checksum .tar.gz: b099841a3f8c0e591ffff295c4aa30b243c3d7cc21446ff5ca2fac52792c34ea
Checksum .whl: 7de3bd267176b9b2a8defb6997c1cd296da16c57b5e712f72ea44a51755421c8

Details: https://spacy.io/models/zh#zh_core_web_sm

Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler.

Feature Description
Name zh_core_web_sm
Version 3.8.0
spaCy >=3.8.0,<3.9.0
Default Pipeline tok2vec, tagger, parser, attribute_ruler, ner
Components tok2vec, tagger, parser, senter, attribute_ruler, ner
Vectors 0 keys, 0 unique vectors (0 dimensions)
Sources OntoNotes 5 (Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, Ann Houston)
CoreNLP Universal Dependencies Converter (Stanford NLP Group)
License MIT
Author Explosion
Model size 46 MB

Label Scheme

View label scheme (100 labels for 3 components) | Component | Labels | | --- | --- | | **`tagger`** | `AD`, `AS`, `BA`, `CC`, `CD`, `CS`, `DEC`, `DEG`, `DER`, `DEV`, `DT`, `ETC`, `FW`, `IJ`, `INF`, `JJ`, `LB`, `LC`, `M`, `MSP`, `NN`, `NR`, `NT`, `OD`, `ON`, `P`, `PN`, `PU`, `SB`, `SP`, `URL`, `VA`, `VC`, `VE`, `VV`, `X`, `_SP` | | **`parser`** | `ROOT`, `acl`, `advcl:loc`, `advmod`, `advmod:dvp`, `advmod:loc`, `advmod:rcomp`, `amod`, `amod:ordmod`, `appos`, `aux:asp`, `aux:ba`, `aux:modal`, `aux:prtmod`, `auxpass`, `case`, `cc`, `ccomp`, `compound:nn`, `compound:vc`, `conj`, `cop`, `dep`, `det`, `discourse`, `dobj`, `etc`, `mark`, `mark:clf`, `name`, `neg`, `nmod`, `nmod:assmod`, `nmod:poss`, `nmod:prep`, `nmod:range`, `nmod:tmod`, `nmod:topic`, `nsubj`, `nsubj:xsubj`, `nsubjpass`, `nummod`, `parataxis:prnmod`, `punct`, `xcomp` | | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |

Accuracy

Type Score
TOKEN_ACC 95.85
TOKEN_P 94.58
TOKEN_R 91.36
TOKEN_F 92.94
TAG_ACC 89.39
SENTS_P 78.18
SENTS_R 72.90
SENTS_F 75.45
DEP_UAS 69.52
DEP_LAS 64.05
ENTS_P 72.27
ENTS_R 64.97
ENTS_F 68.42

Installation

:::bash
pip install spacy
python -m spacy download zh_core_web_sm
Source: README.md, updated 2024-09-25