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zh_core_web_trf
Ella01/zh_core_web_trf
zh_core_web_trf is a token classification model from Ella01. 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 transformer pipeline (Transformer(name='bert-base-chinese', pieceencoder='bert-wordpiece', stride=152, type='bert', width=768, window=208, vocabsize=21128)). Components: transformer, tagger, parser, ner, attri…
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At a glance
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Jun 26, 2024
- Updated
- Jun 27, 2024
- SHA
- b58e640e
Try a prompt
Model card
From the Hugging Face model README
Chinese transformer pipeline (Transformer(name='bert-base-chinese', piece_encoder='bert-wordpiece', stride=152, type='bert', width=768, window=208, vocab_size=21128)). Components: transformer, tagger, parser, ner, attribute_ruler.
| Feature | Description |
|---|---|
| Name | zh_core_web_trf |
| Version | 3.7.2 |
| spaCy | >=3.7.0,<3.8.0 |
| Default Pipeline | transformer, tagger, parser, attribute_ruler, ner |
| Components | transformer, tagger, parser, 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)<br>CoreNLP Universal Dependencies Converter (Stanford NLP Group)<br>bert-base-chinese (Hugging Face) |
| License | MIT |
| Author | Explosion |
Label Scheme
<details> <summary>View label scheme (99 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 |
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 | 91.75 |
SENTS_P | 70.92 |
SENTS_R | 67.57 |
SENTS_F | 69.21 |
DEP_UAS | 75.72 |
DEP_LAS | 71.45 |
ENTS_P | 76.09 |
ENTS_R | 72.18 |
ENTS_F | 74.08 |
- Task
- Token Classification
- Library
- spacy
- Type
- bert
- License
- mit
- Languages
- zh
- Created
- Jun 26, 2024
- Updated
- Jun 27, 2024