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