(num_labels, args)
| 28 | from peft.utils import _get_submodules |
| 29 | |
| 30 | def create_model_tokenizer(num_labels, args): |
| 31 | |
| 32 | if 'roberta' in args.model: |
| 33 | |
| 34 | model = AutoModelForSequenceClassification.from_pretrained(args.model, num_labels=num_labels) |
| 35 | tokenizer = AutoTokenizer.from_pretrained(args.model) |
| 36 | |
| 37 | model.to(args.device) |
| 38 | |
| 39 | return model, tokenizer |
| 40 | |
| 41 | |
| 42 | def create_peft_model(model, args): |