readme: ---
  language: ar
  datasets:
  - HARD-Arabic-Dataset
  ---
  # Ara-dialect-BERT
  We used a pretrained model to further train it on [HARD-Arabic-Dataset](https://github.com/elnagara/HARD-Arabic-Dataset), the weights were initialized using [CAMeL-Lab](https://huggingface.co/CAMeL-Lab/bert-base-camelbert-msa-eighth) "bert-base-camelbert-msa-eighth" model
  
  
  ### Usage
  The model weights can be loaded using `transformers` library by HuggingFace.
  ```python
  from transformers import AutoTokenizer, AutoModel
  tokenizer = AutoTokenizer.from_pretrained("MutazYoune/Ara_DialectBERT")
  model = AutoModel.from_pretrained("MutazYoune/Ara_DialectBERT")
  ```
  Example using `pipeline`:
  ```python
  from transformers import pipeline
  fill_mask = pipeline(
      "fill-mask",
      model="MutazYoune/Ara_DialectBERT",
      tokenizer="MutazYoune/Ara_DialectBERT"
  )
  fill_mask("الفندق جميل و لكن [MASK] بعيد")
  ```
  ```python
  {'sequence': 'الفندق جميل و لكن الموقع بعيد', 'score': 0.28233852982521057, 'token': 3221, 'token_str': 'الموقع'}
  {'sequence': 'الفندق جميل و لكن موقعه بعيد', 'score': 0.24436227977275848, 'token': 19218, 'token_str': 'موقعه'}
  {'sequence': 'الفندق جميل و لكن المكان بعيد', 'score': 0.15372352302074432, 'token': 5401, 'token_str': 'المكان'}
  {'sequence': 'الفندق جميل و لكن الفندق بعيد', 'score': 0.029026474803686142, 'token': 11133, 'token_str': 'الفندق'}
  {'sequence': 'الفندق جميل و لكن مكانه بعيد', 'score': 0.024554792791604996, 'token': 10701, 'token_str': 'مكانه'}
  