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on
Zero
Running
on
Zero
| 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): | |
| # text = "Replace me by any text you'd like." | |
| 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): | |
| # text = "Replace me by any text you'd like." | |
| 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): | |
| # text = "Replace me by any text you'd like." | |
| encoded_input = tokenizer(text, return_tensors="pt") | |
| output = model(**encoded_input) | |
| return output | |