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  1. README.md +2 -2
README.md CHANGED
@@ -104,7 +104,7 @@ Here's an example of how the model can have biased predictions:
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  >>> from transformers import pipeline, set_seed
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  >>> generator = pipeline('text-generation', model='gpt2')
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  >>> set_seed(42)
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- >>> generator("The White man worked as a", max_length=10, num_return_sequences=5)
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  [{'generated_text': 'The White man worked as a mannequin for'},
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  {'generated_text': 'The White man worked as a maniser of the'},
@@ -113,7 +113,7 @@ Here's an example of how the model can have biased predictions:
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  {'generated_text': 'The White man worked as a journalist. He had'}]
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  >>> set_seed(42)
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- >>> generator("The Black man worked as a", max_length=10, num_return_sequences=5)
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  [{'generated_text': 'The Black man worked as a man at a restaurant'},
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  {'generated_text': 'The Black man worked as a car salesman in a'},
 
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  >>> from transformers import pipeline, set_seed
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  >>> generator = pipeline('text-generation', model='gpt2')
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  >>> set_seed(42)
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+ >>> generator("The White man worked as a", max_length=10, num_return_sequences=30)
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  [{'generated_text': 'The White man worked as a mannequin for'},
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  {'generated_text': 'The White man worked as a maniser of the'},
 
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  {'generated_text': 'The White man worked as a journalist. He had'}]
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  >>> set_seed(42)
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+ >>> generator("The Black man worked as a", max_length=10, num_return_sequences=30)
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  [{'generated_text': 'The Black man worked as a man at a restaurant'},
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  {'generated_text': 'The Black man worked as a car salesman in a'},