Create code/peft/peft_example.py

code/peft/peft_example.py

@@ -0,0 +1,27 @@
+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")