readme: ---
  language:
  - hi
  - en
  - multilingual
  license: mit
  tags:
  - codeswitching
  - hindi-english
  - ner
  datasets:
  - lince
  ---
  
  # codeswitch-hineng-ner-lince
  This is a pretrained model for **Name Entity Recognition** of `Hindi-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
  
  This model is trained for this below repository. 
  
  [https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
  
  To install codeswitch:
  
  ```
  pip install codeswitch
  ```
  
  ## Name Entity Recognition of Code-Mixed Data
  
  * **Method-1**
  
  ```py
  
  from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
  
  tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-hineng-ner-lince")
  
  model = AutoModelForTokenClassification.from_pretrained("sagorsarker/codeswitch-hineng-ner-lince")
  
  ner_model = pipeline('ner', model=model, tokenizer=tokenizer)
  
  ner_model("put any hindi english code-mixed sentence")
  
  ```
  
  * **Method-2**
  
  ```py
  from codeswitch.codeswitch import NER
  ner = NER('hin-eng')
  text = "" # your mixed sentence 
  result = ner.tag(text)
  print(result)
  
  ```
  