ldm/modules/encoders/open_clap/bert.py

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