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en_docusco_spacy
browndw/en_docusco_spacy
en_docusco_spacy is a token classification model from browndw. 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 for part-of-speech and rhetorical tagging.
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Repo size
146 MB
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4
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Repo makeup
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.json11.9 MB · 44%
At a glance
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Access
- Public
- Created
- Mar 23, 2022
- Updated
- Jan 7, 2026
- SHA
- da4a88b4
Try a prompt
Model card
From the Hugging Face model README
English pipeline for part-of-speech and rhetorical tagging.
| Feature | Description |
|---|---|
| Name | en_docusco_spacy |
| Version | 1.5 |
| spaCy | >=3.8.6,<3.9.0 |
| Default Pipeline | tok2vec, tagger, ner |
| Components | tok2vec, tagger, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | MIT |
| Author | David Brown |
Installation
pip install "en_docusco_spacy @ https://huggingface.co/browndw/en_docusco_spacy/resolve/main/en_docusco_spacy-1.5-py3-none-any.whl"
Note that per naming requirements the wheel has the version number in place of any: en_docusco_spacy-<version>-py3-none-any
Label Scheme
<details> <summary>View label scheme (311 labels for 2 components)</summary>| Component | Labels |
|---|---|
tagger | APPGE, AT, AT1, BCL21, BCL22, CC, CCB, CS, CS21, CS22, CS31, CS32, CS33, CS41, CS42, CS43, CS44, CSA, CSN, CST, CSW, CSW31, CSW32, CSW33, DA, DA1, DA2, DAR, DAT, DB, DB2, DD, DD1, DD2, DDQ, DDQGE, DDQGE31, DDQGE32, DDQGE33, DDQV, DDQV31, DDQV32, DDQV33, EX, FO, FU, FW, GE, IF, II, II21, II22, II31, II32, II33, II41, II42, II43, II44, IO, IW, JJ, JJ21, JJ22, JJ31, JJ32, JJ33, JJ41, JJ42, JJ43, JJ44, JJR, JJT, JK, MC, MC1, MC121, MC122, MC2, MC221, MC222, MCMC, MD, MF, ND1, NN, NN1, NN121, NN122, NN131, NN132, NN133, NN141, NN142, NN143, NN144, NN2, NN21, NN22, NN221, NN222, NN31, NN32, NN33, NNA, NNB, NNL1, NNL2, NNO, NNO2, NNT1, NNT131, NNT132, NNT133, NNT2, NNU, NNU1, NNU2, NNU21, NNU22, NNU221, NNU222, NP, NP1, NP2, NPD1, NPD2, NPM1, NPM2, PN, PN1, PN121, PN122, PN21, PN22, PNQO, PNQS, PNQS31, PNQS32, PNQS33, PNQV, PNQV31, PNQV32, PNQV33, PNX1, PPGE, PPH1, PPHO1, PPHO2, PPHS1, PPHS2, PPIO1, PPIO2, PPIS1, PPIS2, PPX1, PPX121, PPX122, PPX2, PPX221, PPX222, PPY, RA, RA21, RA22, REX, REX21, REX22, REX41, REX42, REX43, REX44, RG, RG21, RG22, RG31, RG32, RG33, RG41, RG42, RG43, RG44, RGQ, RGQV, RGQV31, RGQV32, RGQV33, RGR, RGT, RL, RL21, RL22, RL31, RL32, RL33, RP, RPK, RR, RR21, RR22, RR31, RR32, RR33, RR41, RR42, RR43, RR44, RR51, RR52, RR53, RR54, RR55, RRQ, RRQV, RRQV31, RRQV32, RRQV33, RRR, RRT, RT, RT21, RT22, RT31, RT32, RT33, RT41, RT42, RT43, RT44, TO, UH, UH21, UH22, UH31, UH32, UH33, VB0, VBDR, VBDZ, VBG, VBI, VBM, VBN, VBR, VBZ, VD0, VDD, VDG, VDI, VDN, VDZ, VH0, VHD, VHG, VHI, VHN, VHZ, VM, VM21, VM22, VMK, VV0, VVD, VVG, VVGK, VVI, VVN, VVNK, VVZ, XX, Y, ZZ1, ZZ2, ZZ221, ZZ222 |
ner | AcademicTerms, AcademicWritingMoves, Character, Citation, CitationAuthority, CitationHedged, ConfidenceHedged, ConfidenceHigh, ConfidenceLow, Contingent, Description, Facilitate, FirstPerson, ForceStressed, Future, InformationChange, InformationChangeNegative, InformationChangePositive, InformationExposition, InformationPlace, InformationReportVerbs, InformationStates, InformationTopics, Inquiry, Interactive, MetadiscourseCohesive, MetadiscourseInteractive, Narrative, Negative, Positive, PublicTerms, Reasoning, Responsibility, Strategic, Uncertainty, Updates |
Accuracy
| Type | Score |
|---|---|
TAG_ACC | 97.38 |
ENTS_F | 80.86 |
ENTS_P | 80.53 |
ENTS_R | 81.19 |
TOK2VEC_LOSS | 415094086.10 |
TAGGER_LOSS | 5414630.50 |
NER_LOSS | 25495485.94 |
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Languages
- en
- Created
- Mar 23, 2022
- Updated
- Jan 7, 2026