| | from transformers import BertTokenizer, BertModel
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| |
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| | tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")
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| | model = BertModel.from_pretrained("bert-base-uncased")
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| | text = "Replace me by any text you'd like."
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| |
|
| |
|
| | def bert_embeddings(text):
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| |
|
| | encoded_input = tokenizer(text, return_tensors="pt")
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| | output = model(**encoded_input)
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| | return output
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| |
|
| |
|
| | from transformers import RobertaTokenizer, RobertaModel
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| |
|
| | tokenizer = RobertaTokenizer.from_pretrained("roberta-base")
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| | model = RobertaModel.from_pretrained("roberta-base")
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| | text = "Replace me by any text you'd like."
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| |
|
| |
|
| | def Roberta_embeddings(text):
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| |
|
| | encoded_input = tokenizer(text, return_tensors="pt")
|
| | output = model(**encoded_input)
|
| | return output
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| |
|
| |
|
| | from transformers import BartTokenizer, BartModel
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| |
|
| | tokenizer = BartTokenizer.from_pretrained("facebook/bart-base")
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| | model = BartModel.from_pretrained("facebook/bart-base")
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| | text = "Replace me by any text you'd like."
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| |
|
| |
|
| | def bart_embeddings(text):
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| |
|
| | encoded_input = tokenizer(text, return_tensors="pt")
|
| | output = model(**encoded_input)
|
| | return output
|
| |
|