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zh_core_web_md
spacy/zh_core_web_md
zh_core_web_md is a token classification model from spacy. Use it when you need labels on individual words, such as names. It is set up for spacy. The card lists the license as mit.
Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attributeruler.
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Repo size
818 MB
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At a glance
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Oct 10, 2023
- SHA
- 81b478c0
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Model card
From the Hugging Face model README
Details: https://spacy.io/models/zh#zh_core_web_md
Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler.
| Feature | Description |
|---|---|
| Name | zh_core_web_md |
| Version | 3.7.0 |
| spaCy | >=3.7.0,<3.8.0 |
| Default Pipeline | tok2vec, tagger, parser, attribute_ruler, ner |
| Components | tok2vec, tagger, parser, senter, attribute_ruler, ner |
| Vectors | 500000 keys, 20000 unique vectors (300 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)<br />CoreNLP Universal Dependencies Converter (Stanford NLP Group)<br />Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia) (Explosion) |
| License | MIT |
| Author | Explosion |
Label Scheme
<details> <summary>View label scheme (100 labels for 3 components)</summary>| 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 | 90.04 |
SENTS_P | 78.89 |
SENTS_R | 72.80 |
SENTS_F | 75.72 |
DEP_UAS | 70.50 |
DEP_LAS | 65.22 |
ENTS_P | 71.88 |
ENTS_R | 67.90 |
ENTS_F | 69.83 |
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Languages
- zh
- Created
- Mar 2, 2022
- Updated
- Oct 10, 2023