readme: 
  #### How to use
  You can use this model with Transformers *pipeline* for NER.
  ```python
  from transformers import AutoTokenizer, AutoModelForTokenClassification
  from transformers import pipeline
  tokenizer = AutoTokenizer.from_pretrained("Holako/NER_model_holako")
  model = AutoModelForTokenClassification.from_pretrained("Holako/NER_model_holako")
  nlp = pipeline("ner", model=model, tokenizer=tokenizer)
  example = "اسمي احمد"
  ner_results = nlp(example)
  print(ner_results)
  ```
  #### Limitations and bias
  This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may not generalize well for all use cases in different domains.  
  
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  #### Limitations and bias
  This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may not generalize well for all use cases in different domains.  
  ## Training data
  
  Language|Dataset
  -|-
  Arabic | [ANERcorp](https://camel.abudhabi.nyu.edu/anercorp/)
  