Update tiny models and a few fixes (#22928)

* run_check_tiny_models

* update summary

* update mixin

* update pipeline_model_mapping

* update pipeline_model_mapping

* Update for gpt_bigcode

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

tests/models/sam/test_modeling_sam.py

@@ -26,6 +26,7 @@ from transformers.utils import is_torch_available, is_vision_available
 
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, floats_tensor
+from ...test_pipeline_mixin import PipelineTesterMixin
 
 
 if is_torch_available():
@@ -282,19 +283,28 @@ class SamModelTester:
 
 
 @require_torch
-class SamModelTest(ModelTesterMixin, unittest.TestCase):
+class SamModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     """
     Here we also overwrite some of the tests of test_modeling_common.py, as SAM's vision encoder does not use input_ids, inputs_embeds,
     attention_mask and seq_length.
     """
 
     all_model_classes = (SamModel,) if is_torch_available() else ()
+    pipeline_model_mapping = (
+        {"feature-extraction": SamModel, "mask-generation": SamModel} if is_torch_available() else {}
+    )
     fx_compatible = False
     test_pruning = False
     test_resize_embeddings = False
     test_head_masking = False
     test_torchscript = False
 
+    # TODO: Fix me @Arthur: `run_batch_test` in `tests/test_pipeline_mixin.py` not working
+    def is_pipeline_test_to_skip(
+        self, pipeline_test_casse_name, config_class, model_architecture, tokenizer_name, processor_name
+    ):
+        return True
+
     def setUp(self):
         self.model_tester = SamModelTester(self)
         self.vision_config_tester = ConfigTester(self, config_class=SamVisionConfig, has_text_modality=False)