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| from transformers import pipeline | |
| def squeezebert(context, question): | |
| # Define the specific model and tokenizer for SqueezeBERT | |
| model_name = "ALOQAS/squeezebert-uncased-finetuned-squad-v2" | |
| pip = pipeline('question-answering', model=model_name, tokenizer=model_name) | |
| return pip(context=context, question=question) | |
| def bert(context, question): | |
| # Define the specific model and tokenizer for BERT | |
| model_name = "ALOQAS/bert-large-uncased-finetuned-squad-v2" | |
| pip = pipeline('question-answering', model=model_name, tokenizer=model_name) | |
| return pip(context=context, question=question) | |
| def deberta(context, question): | |
| # Define the specific model and tokenizer for DeBERTa | |
| model_name = "ALOQAS/deberta-large-finetuned-squad-v2" | |
| pip = pipeline('question-answering', model=model_name, tokenizer=model_name) | |
| return pip(context=context, question=question) | |