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            # CAMeLBERT MSA NER Model
         
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            ## Model description
         
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            **CAMeLBERT MSA NER Model** is a Named Entity Recognition (NER) model that was built by fine-tuning the [CAMeLBERT Modern Standard Arabic (MSA)](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa/) model. 
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            ## Intended uses
         
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            You can use the CAMeLBERT MSA NER model directly as part of our [CAMeL Tools](https://github.com/CAMeL-Lab/camel_tools) NER component (*recommended*) or as part of the transformers pipeline.
         
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            >>> ['O', 'B-LOC', 'O', 'O', 'O', 'O', 'B-LOC', 'I-LOC', 'I-LOC', 'O']
         
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            ```
         
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            You can also use the NER model directly with a transformers pipeline:
         
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            ```python
         
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            >>> from transformers import pipeline
         
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              'start': 50,
         
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              'end': 57}]
         
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            ```
         
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            *Note*: to download our models, you would need `transformers>=3.5.0`. 
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            ## Citation
         
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            ```bibtex
         
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            ---
         
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            # CAMeLBERT MSA NER Model
         
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            ## Model description
         
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            **CAMeLBERT MSA NER Model** is a Named Entity Recognition (NER) model that was built by fine-tuning the [CAMeLBERT Modern Standard Arabic (MSA)](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa/) model.
         
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            For the fine-tuning, we used the [ANERcorp](https://camel.abudhabi.nyu.edu/anercorp/) dataset.
         
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            Our fine-tuning procedure and the hyperparameters we used can be found in our paper *"[The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models](https://arxiv.org/abs/2103.06678).
         
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            "* Our fine-tuning code can be found [here](https://github.com/CAMeL-Lab/CAMeLBERT).
         
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            ## Intended uses
         
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            You can use the CAMeLBERT MSA NER model directly as part of our [CAMeL Tools](https://github.com/CAMeL-Lab/camel_tools) NER component (*recommended*) or as part of the transformers pipeline.
         
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            >>> ['O', 'B-LOC', 'O', 'O', 'O', 'O', 'B-LOC', 'I-LOC', 'I-LOC', 'O']
         
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            ```
         
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            You can also use the NER model directly with a transformers pipeline:
         
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            ```python
         
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            >>> from transformers import pipeline
         
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              'start': 50,
         
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              'end': 57}]
         
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            ```
         
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            *Note*: to download our models, you would need `transformers>=3.5.0`.
         
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            Otherwise, you could download the models manually.
         
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            ## Citation
         
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            ```bibtex
         
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