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  + **Bias**: Significant research has explored bias and fairness issues with language models. Predictions generated by this model may contain biases, including harmful stereotypes related to protected classes, identity characteristics, and sensitive social and occupational groups.
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  + **Fairness**: It's essential to be aware of fairness considerations when using this model and to ensure that its predictions do not contribute to unfair or harmful outcomes.
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- + **Ethical Use**: Users are encouraged to use this model ethically and responsibly, taking into account the potential for bias and ensuring that it does not generate harmful or offensive content.
 
 
 
 
 
 
 
 
 
 
 
 
 
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  + **Bias**: Significant research has explored bias and fairness issues with language models. Predictions generated by this model may contain biases, including harmful stereotypes related to protected classes, identity characteristics, and sensitive social and occupational groups.
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  + **Fairness**: It's essential to be aware of fairness considerations when using this model and to ensure that its predictions do not contribute to unfair or harmful outcomes.
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+ + **Ethical Use**: Users are encouraged to use this model ethically and responsibly, taking into account the potential for bias and ensuring that it does not generate harmful or offensive content.
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+
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+ + ## Usage :
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+ ```python
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+ # Use a pipeline as a high-level helper
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+ from transformers import pipeline
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+
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+ pipe = pipeline("fill-mask", model="ayoubkirouane/FILL-MAsk-RoBERTa-base")
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+ result = pipe("The capital of Algeria is <mask>.")
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+ print(result)
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+ ```