Instructions to use TakoData/en_tako_query_analyzer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use TakoData/en_tako_query_analyzer with spaCy:
!pip install https://huggingface.co/TakoData/en_tako_query_analyzer/resolve/main/en_tako_query_analyzer-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_tako_query_analyzer") # Importing as module. import en_tako_query_analyzer nlp = en_tako_query_analyzer.load() - Notebooks
- Google Colab
- Kaggle
Download meta.json from TakoData/en_tako_query_analyzer: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/TakoData/en_tako_query_analyzer/resolve/main/meta.json
- Command line
-
hf download hf://TakoData/en_tako_query_analyzer/meta.json
-
curl -L -o meta.json https://huggingface.co/TakoData/en_tako_query_analyzer/resolve/main/meta.json
3.39 kB
| { | |
| "lang":"en", | |
| "name":"tako_query_analyzer", | |
| "version":"0.0.5", | |
| "description":"", | |
| "author":"", | |
| "email":"", | |
| "url":"", | |
| "license":"", | |
| "spacy_version":">=3.8.11,<3.9.0", | |
| "spacy_git_version":"e7a662a", | |
| "vectors":{ | |
| "width":300, | |
| "vectors":342918, | |
| "keys":684830, | |
| "name":"en_vectors" | |
| }, | |
| "labels":{ | |
| "tok2vec_small":[ | |
| ], | |
| "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" | |
| ], | |
| "attribute_ruler":[ | |
| ], | |
| "tok2vec":[ | |
| ], | |
| "ner":[ | |
| "CARDINAL", | |
| "DATE", | |
| "EVENT", | |
| "FAC", | |
| "GPE", | |
| "LANGUAGE", | |
| "LAW", | |
| "LOC", | |
| "MONEY", | |
| "NORP", | |
| "ORDINAL", | |
| "ORG", | |
| "PERCENT", | |
| "PERSON", | |
| "PRODUCT", | |
| "QUANTITY", | |
| "STOCK_TICKER", | |
| "TIME", | |
| "WORK_OF_ART" | |
| ], | |
| "textcat_multilabel":[ | |
| "Finance", | |
| "Economics", | |
| "Demographics", | |
| "Health", | |
| "Politics", | |
| "Sports", | |
| "Climate", | |
| "Other" | |
| ], | |
| "textcat_classify":[ | |
| "ACCEPT", | |
| "REJECT" | |
| ] | |
| }, | |
| "pipeline":[ | |
| "tok2vec_small", | |
| "tagger", | |
| "parser", | |
| "attribute_ruler", | |
| "senter", | |
| "tok2vec", | |
| "ner", | |
| "textcat_multilabel", | |
| "textcat_classify" | |
| ], | |
| "components":[ | |
| "tok2vec_small", | |
| "tagger", | |
| "parser", | |
| "attribute_ruler", | |
| "senter", | |
| "tok2vec", | |
| "ner", | |
| "textcat_multilabel", | |
| "textcat_classify" | |
| ], | |
| "disabled":[ | |
| ], | |
| "performance":{ | |
| "ents_f":0.0, | |
| "ents_p":0.0, | |
| "ents_r":0.0, | |
| "ents_per_type":0.0, | |
| "cats_score":0.8462255359, | |
| "cats_score_desc":"F (ACCEPT)", | |
| "cats_micro_p":0.835, | |
| "cats_micro_r":0.835, | |
| "cats_micro_f":0.835, | |
| "cats_macro_p":0.8422963898, | |
| "cats_macro_r":0.835, | |
| "cats_macro_f":0.8341160042, | |
| "cats_macro_auc":0.83958575, | |
| "cats_f_per_type":{ | |
| "ACCEPT":{ | |
| "p":0.7923211169, | |
| "r":0.908, | |
| "f":0.8462255359 | |
| }, | |
| "REJECT":{ | |
| "p":0.8922716628, | |
| "r":0.762, | |
| "f":0.8220064725 | |
| } | |
| }, | |
| "textcat_classify_loss":11.0869617185 | |
| }, | |
| "requirements":[ | |
| "spacy>=3.8.11,<3.9.0" | |
| ] | |
| } |