Update README.md
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README.md
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@@ -91,7 +91,7 @@ logits = model.run(output_names=output_names, input_feed=input_feed_dict)[0]
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# produces a numpy array, one row per input item, one col per label
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# Post-processing. Gets the scores per label in range.
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# Auto done by Transformers' pipeline, but we must
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model_outputs = sigmoid(logits)
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# for example, just to show the top result per input item
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# produces a numpy array, one row per input item, one col per label
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# Post-processing. Gets the scores per label in range.
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# Auto done by Transformers' pipeline, but we must do it manually with ORT.
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model_outputs = sigmoid(logits)
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# for example, just to show the top result per input item
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