Checksum .tar.gz:
ecb0526630a1a05b2a2df6636bd8059bd0b4cb2280e91708f03f7838d14d0be7
Checksum .whl:8902305d2ced83d98a8e88efd93ea8970a70dda9bb24b0024a8b798d1cc913d5
Details: https://spacy.io/models/en#en_core_web_trf
English transformer pipeline (roberta-base). Components: transformer, tagger, parser, ner, attribute_ruler, lemmatizer.
Feature | Description |
---|---|
Name | en_core_web_trf
|
Version | 3.5.0
|
spaCy | >=3.5.0,<3.6.0
|
Default Pipeline | transformer , tagger , parser , attribute_ruler , lemmatizer , ner
|
Components | transformer , tagger , parser , attribute_ruler , lemmatizer , 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) ClearNLP Constituent-to-Dependency Conversion (Emory University) WordNet 3.0 (Princeton University) roberta-base (Yinhan Liu and Myle Ott and Naman Goyal and Jingfei Du and Mandar Joshi and Danqi Chen and Omer Levy and Mike Lewis and Luke Zettlemoyer and Veselin Stoyanov) |
License | MIT
|
Author | Explosion |
Model size | 438 MB |
Label Scheme
View label scheme (112 labels for 3 components)
Component | Labels |
---|---|
tagger
| $ , '' , , , -LRB- , -RRB- , . , : , ADD , AFX , CC , CD , DT , EX , FW , HYPH , IN , JJ , JJR , JJS , LS , MD , NFP , NN , NNP , NNPS , NNS , PDT , POS , PRP , PRP$ , RB , RBR , RBS , RP , SYM , TO , UH , VB , VBD , VBG , VBN , VBP , VBZ , WDT , WP , WP$ , WRB , XX , ````
|
parser
| ROOT , acl , acomp , advcl , advmod , agent , amod , appos , attr , aux , auxpass , case , cc , ccomp , compound , conj , csubj , csubjpass , dative , dep , det , dobj , expl , intj , mark , meta , neg , nmod , npadvmod , nsubj , nsubjpass , nummod , oprd , parataxis , pcomp , pobj , poss , preconj , predet , prep , prt , punct , quantmod , relcl , 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
| 99.86 |
TOKEN_P
| 99.57 |
TOKEN_R
| 99.58 |
TOKEN_F
| 99.57 |
TAG_ACC
| 97.79 |
SENTS_P
| 95.04 |
SENTS_R
| 84.92 |
SENTS_F
| 89.69 |
DEP_UAS
| 95.27 |
DEP_LAS
| 93.95 |
ENTS_P
| 89.78 |
ENTS_R
| 90.49 |
ENTS_F
| 90.13 |
Installation
pip install spacy
python -m spacy download en_core_web_trf