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@@ -29,8 +29,8 @@ The easiest way is to load through the pipeline object offered by transformers l
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  ```python
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  from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
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  from transformers import pipeline
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- tokenizer = AutoTokenizer.from_pretrained("d4data/bias-detection-model")
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- model = TFAutoModelForSequenceClassification.from_pretrained("d4data/bias-detection-model")
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  classifier = pipeline('text-classification', model=model, tokenizer=tokenizer) # cuda = 0,1 based on gpu availability
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  classifier("The irony, of course, is that the exhibit that invites people to throw trash at vacuuming Ivanka Trump lookalike reflects every stereotype feminists claim to stand against, oversexualizing Ivanka’s body and ignoring her hard work.")
 
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  ```python
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  from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
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  from transformers import pipeline
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+ tokenizer = AutoTokenizer.from_pretrained("d4data/environmental-due-diligence-model")
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+ model = TFAutoModelForSequenceClassification.from_pretrained("d4data/environmental-due-diligence-model")
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  classifier = pipeline('text-classification', model=model, tokenizer=tokenizer) # cuda = 0,1 based on gpu availability
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  classifier("The irony, of course, is that the exhibit that invites people to throw trash at vacuuming Ivanka Trump lookalike reflects every stereotype feminists claim to stand against, oversexualizing Ivanka’s body and ignoring her hard work.")