from transformers import AutoTokenizer, AutoModelForQuestionAnswering, pipeline
from peft import PeftModel, PeftConfig

config = PeftConfig.from_pretrained("MohamedShakhsak/bert-qa-squad2_V1")
base_model = AutoModelForQuestionAnswering.from_pretrained(config.base_model_name_or_path)
model = PeftModel.from_pretrained(base_model, "MohamedShakhsak/bert-qa-squad2_V1")

tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
qa_pipeline = pipeline("question-answering", model=model, tokenizer=tokenizer)


qa_pipeline = pipeline("question-answering", model=model, tokenizer=tokenizer)

examples = [
    {
        "question": "What is the capital of France?",
        "context": "Paris is the capital and most populous city of France."
    },
    {
        "question": "When was the iPhone first released?",
        "context": "The first iPhone was released by Apple Inc. on June 29, 2007."
    }
]

for example in examples:
    answer = qa_pipeline(example)
    print(f"Q: {example['question']}\nA: {answer}\n")