| 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 |
|
|