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README.md
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Here is how to use this model to get the features of a given text in PyTorch:
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```from transformers import BertTokenizer, BertModel
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tokenizer = BertTokenizer.from_pretrained('tbs17/MathBERT')
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model = BertModel.from_pretrained("tbs17/MathBERT")
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text = "Replace me by any text you'd like."
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encoded_input = tokenizer(text, return_tensors='pt')
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```
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from transformers import BertTokenizer, TFBertModel
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tokenizer = BertTokenizer.from_pretrained('tbs17/MathBERT')
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model = TFBertModel.from_pretrained("tbs17/MathBERT")
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text = "Replace me by any text you'd like."
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encoded_input = tokenizer(text, return_tensors='tf')
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Here is how to use this model to get the features of a given text in PyTorch:
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```from transformers import BertTokenizer, BertModel
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tokenizer = BertTokenizer.from_pretrained('tbs17/MathBERT'，output_hidden_states=True)
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model = BertModel.from_pretrained("tbs17/MathBERT")
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text = "Replace me by any text you'd like."
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encoded_input = tokenizer(text, return_tensors='pt')
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```
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from transformers import BertTokenizer, TFBertModel
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tokenizer = BertTokenizer.from_pretrained('tbs17/MathBERT',output_hidden_states=True)
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model = TFBertModel.from_pretrained("tbs17/MathBERT")
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text = "Replace me by any text you'd like."
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encoded_input = tokenizer(text, return_tensors='tf')
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