Enable auto task for timm models in pipeline (#35531)

* Enable auto task for timm models

* Add pipeline test

src/transformers/pipelines/__init__.py

@@ -494,7 +494,7 @@ def get_task(model: str, token: Optional[str] = None, **deprecated_kwargs) -> st
         raise RuntimeError(
             f"The model {model} does not seem to have a correct `pipeline_tag` set to infer the task automatically"
         )
-    if getattr(info, "library_name", "transformers") != "transformers":
+    if getattr(info, "library_name", "transformers") not in {"transformers", "timm"}:
         raise RuntimeError(f"This model is meant to be used with {info.library_name} not with transformers")
     task = info.pipeline_tag
     return task

tests/models/timm_wrapper/test_modeling_timm_wrapper.py

@@ -17,6 +17,7 @@ import inspect
 import tempfile
 import unittest
 
+from transformers import pipeline
 from transformers.testing_utils import (
     require_bitsandbytes,
     require_timm,
@@ -294,6 +295,19 @@ class TimmWrapperModelIntegrationTest(unittest.TestCase):
         is_close = torch.allclose(resulted_slice, expected_slice, atol=1e-3)
         self.assertTrue(is_close, f"Expected {expected_slice}, but got {resulted_slice}")
 
+    @slow
+    def test_inference_with_pipeline(self):
+        image = prepare_img()
+        classifier = pipeline(model="timm/resnet18.a1_in1k", device=torch_device)
+        result = classifier(image)
+
+        # verify result
+        expected_label = "tabby, tabby cat"
+        expected_score = 0.4329
+
+        self.assertEqual(result[0]["label"], expected_label)
+        self.assertAlmostEqual(result[0]["score"], expected_score, places=3)
+
     @slow
     @require_bitsandbytes
     def test_inference_image_classification_quantized(self):