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Update README.md

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@@ -70,7 +70,6 @@ def mean_pooling(model_output, attention_mask):
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  input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
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  return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)
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-
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  # Sentences we want sentence embeddings for
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  sentences = ['This is an example sentence', 'Each sentence is converted']
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  input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
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  return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)
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  # Sentences we want sentence embeddings for
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  sentences = ['This is an example sentence', 'Each sentence is converted']
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