readme: ---
  tags:
  - flair
  - token-classification
  - sequence-tagger-model
  language: fa
  datasets:
  - UPC-2017
  widget:
  - text: "تمام ایران یک تابستان تنوری را تجربه میکند ."
  ---
  
  ## Persian Part-of-Speech Tagging in Flair
  
  This is the part-of-speech tagging model for Persian that ships with [Flair](https://github.com/flairNLP/flair/).
  
  F1-Score: **??** (UPC-2017)
  
   List of Tags in UPC:
  
  | **tag**  |       **meaning**       |
  |:--------:|:-----------------------:|
  |   ADJ    |        adjective        |
  | ADJ_CMPR |  Comparative adjective  |
  | ADJ_INO  |  Participle adjective   |
  | ADJ_SUP  |  Superlative adjective  |
  | ADJ_VOC  |   Vocative adjective    |
  |   ADV    |         Adverb          |
  | ADV_COMP |  Adverb of comparison   |
  |  ADV_I   | Adverb of interrogation |
  | ADV_LOC  |   Adverb of location    |
  | ADV_NEG  |   Adverb of negation    |
  | ADV_TIME |     Adverb of time      |
  |  CLITIC  |    Accusative marker    |
  |   CON    |       Conjunction       |
  |   DELM   |        Delimiter        |
  |   DET    |       Determiner        |
  |    FW    |      Foreign Word       |
  |   INT    |      Interjection       |
  |   N_PL   |       Plural noun       |
  |  N_SING  |      Singular noun      |
  |   NUM    |         Numeral         |
  |  N_VOC   |      Vocative noun      |
  |    P     |       Preposition       |
  |    PREV      |       Preverbal particle       |
  |    PRO      |       Pronoun       |
  |    SYM     |       Symbol       |
  |    V_AUX     |       Auxiliary verb       |
  |    V_PA     |       Past tense verb       |
  |    V_PP     |       Past participle verb       |
  |    V_PRS     |       Present tense verb       |
  |    V_SUB     |       Subjunctive verb       |
  
  ---
  
  ### Demo: How to use in Flair
  
  Requires: **[Flair](https://github.com/flairNLP/flair/)** (`pip install flair`)
  
  ```python
  from flair.data import Sentence
  from flair.models import SequenceTagger
  
  # load tagger
  tagger = SequenceTagger.load("hamedkhaledi/persain-flair-pos")
  
  # make example sentence
  sentence = Sentence("تمام ایران یک تابستان تنوری را تجربه میکند .")
  
  tagger.predict(sentence)
  # print result
  print(sentence.to_tagged_string())
  ```
  
  This yields the following output:
  
  ```
  تمام <DET> ایران <N_SING> یک <NUM> تابستان <N_SING> تنوری <ADJ> را <CLITIC> تجربه <N_SING> میکند <V_PRS> . <DELM>
  ```