[idefics] idefics-9b test use 4bit quant (#25734)

tests/models/idefics/test_modeling_idefics.py

@@ -16,8 +16,15 @@
 
 import unittest
 
-from transformers import IdeficsConfig, is_torch_available, is_vision_available
-from transformers.testing_utils import TestCasePlus, require_torch, require_vision, slow, torch_device
+from transformers import BitsAndBytesConfig, IdeficsConfig, is_torch_available, is_vision_available
+from transformers.testing_utils import (
+    TestCasePlus,
+    require_bitsandbytes,
+    require_torch,
+    require_vision,
+    slow,
+    torch_device,
+)
 from transformers.utils import cached_property
 
 from ...test_configuration_common import ConfigTester
@@ -434,6 +441,7 @@ class IdeficsModelIntegrationTest(TestCasePlus):
     def default_processor(self):
         return IdeficsProcessor.from_pretrained("HuggingFaceM4/idefics-9b") if is_vision_available() else None
 
+    @require_bitsandbytes
     @slow
     def test_inference_natural_language_visual_reasoning(self):
         cat_image_path = self.tests_dir / "fixtures/tests_samples/COCO/000000039769.png"
@@ -459,7 +467,14 @@ class IdeficsModelIntegrationTest(TestCasePlus):
             ],
         ]
 
-        model = IdeficsForVisionText2Text.from_pretrained("HuggingFaceM4/idefics-9b").to(torch_device)
+        # the CI gpu is small so using quantization to fit
+        quantization_config = BitsAndBytesConfig(
+            load_in_4bit=True,
+            bnb_4bit_compute_dtype="float16",
+        )
+        model = IdeficsForVisionText2Text.from_pretrained(
+            "HuggingFaceM4/idefics-9b", quantization_config=quantization_config, device_map="auto"
+        )
         processor = self.default_processor
         inputs = processor(prompts, return_tensors="pt").to(torch_device)
         generated_ids = model.generate(**inputs, max_length=100)