Fix warning message for PEFT models in text-generation pipeline #36783 (#36887)

* add peft model in constant

* add test

* fix formating

* make fixup execute

* change code

* check by self.task

* add test

* fixup test code

* fix minor typo

* fix pipeline test

* apply maintainers reqests

tests/peft_integration/test_peft_integration.py

@@ -814,3 +814,50 @@ class PeftIntegrationTester(unittest.TestCase, PeftTesterMixin):
                     msg = "When using prompt learning PEFT methods such as PREFIX_TUNING"
                     with self.assertRaisesRegex(RuntimeError, msg):
                         trainer.train()
+
+    def test_peft_pipeline_no_warning(self):
+        """
+        Test to verify that the warning message "The model 'PeftModel' is not supported for text-generation"
+        does not appear when using PeftModel with text-generation pipeline.
+        """
+        from peft import PeftModel
+
+        from transformers import pipeline
+
+        ADAPTER_PATH = "peft-internal-testing/tiny-OPTForCausalLM-lora"
+        BASE_PATH = "hf-internal-testing/tiny-random-OPTForCausalLM"
+
+        # Input text for testing
+        text = "Who is a Elon Musk?"
+        expected_error_msg = "The model 'PeftModel' is not supported for text-generation"
+
+        model = AutoModelForCausalLM.from_pretrained(
+            BASE_PATH,
+            device_map="auto",
+        )
+        tokenizer = AutoTokenizer.from_pretrained(BASE_PATH)
+
+        lora_model = PeftModel.from_pretrained(
+            model,
+            ADAPTER_PATH,
+            device_map="auto",
+        )
+
+        # Create pipeline with PEFT model while capturing log output
+        # Check that the warning message is not present in the logs
+        pipeline_logger = logging.get_logger("transformers.pipelines.base")
+        with self.assertNoLogs(pipeline_logger, logging.ERROR) as cl:
+            lora_generator = pipeline(
+                task="text-generation",
+                model=lora_model,
+                tokenizer=tokenizer,
+                max_length=10,
+            )
+
+            # Generate text to verify pipeline works
+            _ = lora_generator(text)
+
+        # Check that the warning message is not present in the logs
+        self.assertNotIn(
+            expected_error_msg, cl.out, f"Error message '{expected_error_msg}' should not appear when using PeftModel"
+        )