Details: https://spacy.io/models/en#en_core_web_md
Checksum .tar.gz:
45757583a3c9d15c6895cf4bf9512e86243bab8cda51512c127f5cbdc34ac630
Checksum .whl:8b8e01146ab3ac6b5b8f7ed9484c46ece78e755970800f90c203abb7a0c32770
English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler, lemmatizer.
| Feature | Description |
|---|---|
| Name | en_core_web_md
|
| Version | 3.0.0
|
| spaCy | >=3.0.0,<3.1.0
|
| Model size | 44 MB |
| Default Pipeline | tok2vec, tagger, parser, ner, attribute_ruler, lemmatizer
|
| Components | tok2vec, tagger, parser, senter, ner, attribute_ruler, lemmatizer
|
| Vectors | 684830 keys, 20000 unique vectors (300 dimensions) |
| Sources | OntoNotes 5 |
| License | MIT
|
| Author | Explosion |
Label Scheme
View label scheme (114 labels for 4 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
|
senter
| I, S
|
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
| 99.93 |
TAG_ACC
| 97.33 |
DEP_UAS
| 91.97 |
DEP_LAS
| 90.15 |
ENTS_P
| 85.55 |
ENTS_R
| 84.77 |
ENTS_F
| 85.16 |
SENTS_P
| 90.06 |
SENTS_R
| 88.01 |
SENTS_F
| 89.02 |
Installation
pip install spacy
python -m spacy download en_core_web_md