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en_core_web_md
spacy/en_core_web_md
en_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.
English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attributeruler, lemmatizer.
All-time downloads
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Repo size
642 MB
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8
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At a glance
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Nov 21, 2023
- SHA
- 22f17ee2
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Model card
From the Hugging Face model README
Details: https://spacy.io/models/en#en_core_web_md
English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler, lemmatizer.
| Feature | Description |
|---|---|
| Name | en_core_web_md |
| Version | 3.7.1 |
| spaCy | >=3.7.2,<3.8.0 |
| Default Pipeline | tok2vec, tagger, parser, attribute_ruler, lemmatizer, ner |
| Components | tok2vec, tagger, parser, senter, attribute_ruler, lemmatizer, ner |
| Vectors | 514157 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 />ClearNLP Constituent-to-Dependency Conversion (Emory University)<br />WordNet 3.0 (Princeton University)<br />Explosion Vectors (OSCAR 2109 + Wikipedia + OpenSubtitles + WMT News Crawl) (Explosion) |
| License | MIT |
| Author | Explosion |
Label Scheme
<details> <summary>View label scheme (113 labels for 3 components)</summary>| 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, _SP, ```` |
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 | 97.33 |
SENTS_P | 92.21 |
SENTS_R | 89.37 |
SENTS_F | 90.77 |
DEP_UAS | 92.05 |
DEP_LAS | 90.23 |
ENTS_P | 84.94 |
ENTS_R | 85.49 |
ENTS_F | 85.22 |
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Nov 21, 2023