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Update README.md

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@@ -7,6 +7,35 @@ library_name: peft
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  <!-- Provide a quick summary of what the model is/does. -->
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  ## Model Details
 
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  <!-- Provide a quick summary of what the model is/does. -->
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+ ## How to Use
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+
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+ ```python
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+ from transformers import AutoTokenizer, AutoModelForQuestionAnswering, pipeline
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+ from peft import PeftModel, PeftConfig
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+
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+ config = PeftConfig.from_pretrained("MohamedShakhsak/bert-qa-squad2_V1")
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+ base_model = AutoModelForQuestionAnswering.from_pretrained(config.base_model_name_or_path)
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+ model = PeftModel.from_pretrained(base_model, "MohamedShakhsak/bert-qa-squad2_V1")
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+
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+ tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
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+ qa_pipeline = pipeline("question-answering", model=model, tokenizer=tokenizer)
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+
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+ examples = [
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+ {
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+ "question": "What is the capital of France?",
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+ "context": "Paris is the capital and most populous city of France."
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+ },
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+ {
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+ "question": "When was the iPhone first released?",
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+ "context": "The first iPhone was released by Apple Inc. on June 29, 2007."
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+ }
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+ ]
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+
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+ for example in examples:
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+ answer = qa_pipeline(example)
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+ print(f"Q: {example['question']}\nA: {answer}\n")
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+ ```
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+
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  ## Model Details