Use another repo. for Mistral3 processor testing (huggingface#36925)

* fix

* fix

* fix

* fix

---------

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

Author: ydshieh

tests/models/mistral3/test_modeling_mistral3.py

@@ -25,6 +25,7 @@
 from transformers.testing_utils import (
     cleanup,
     require_bitsandbytes,
+    require_read_token,
     require_torch,
     require_torch_gpu,
     slow,
@@ -315,6 +316,7 @@ def setUp(self):
     def tearDown(self):
         cleanup(torch_device, gc_collect=True)
 
+    @require_read_token
     def test_mistral3_integration_generate_text_only(self):
         processor = AutoProcessor.from_pretrained(self.model_checkpoint)
         model = Mistral3ForConditionalGeneration.from_pretrained(
@@ -342,6 +344,7 @@ def test_mistral3_integration_generate_text_only(self):
         expected_output = "Sure, here's a haiku for you:\n\nWhispers of the breeze,\nCherry blossoms softly fall,\nSpring's gentle embrace."
         self.assertEqual(decoded_output, expected_output)
 
+    @require_read_token
     def test_mistral3_integration_generate(self):
         processor = AutoProcessor.from_pretrained(self.model_checkpoint)
         model = Mistral3ForConditionalGeneration.from_pretrained(
@@ -368,6 +371,7 @@ def test_mistral3_integration_generate(self):
         expected_output = "The image depicts two cats lying on a pink blanket. The larger cat, which appears to be an"
         self.assertEqual(decoded_output, expected_output)
 
+    @require_read_token
     def test_mistral3_integration_batched_generate(self):
         processor = AutoProcessor.from_pretrained(self.model_checkpoint)
         model = Mistral3ForConditionalGeneration.from_pretrained(
@@ -418,6 +422,7 @@ def test_mistral3_integration_batched_generate(self):
             f"Decoded output: {decoded_output}\nExpected output: {expected_output}",
         )
 
+    @require_read_token
     @require_bitsandbytes
     def test_mistral3_integration_batched_generate_multi_image(self):
         processor = AutoProcessor.from_pretrained(self.model_checkpoint)

tests/models/mistral3/test_processor_mistral3.py

@@ -20,7 +20,7 @@
 import requests
 
 from transformers import PixtralProcessor
-from transformers.testing_utils import require_read_token, require_vision
+from transformers.testing_utils import require_vision
 from transformers.utils import is_torch_available, is_vision_available
 
 from ...test_processing_common import ProcessorTesterMixin
@@ -35,7 +35,6 @@
 
 
 @require_vision
-@require_read_token
 class Mistral3ProcessorTest(ProcessorTesterMixin, unittest.TestCase):
     """This tests Pixtral processor with the new `spatial_merge_size` argument in Mistral3."""
 
@@ -52,7 +51,9 @@ def setUpClass(cls):
 
     def setUp(self):
         self.tmpdirname = tempfile.mkdtemp()
-        processor = self.processor_class.from_pretrained("mistralai/Mistral-Small-3.1-24B-Instruct-2503")
+        processor = PixtralProcessor.from_pretrained(
+            "hf-internal-testing/Mistral-Small-3.1-24B-Instruct-2503-only-processor"
+        )
         processor.save_pretrained(self.tmpdirname)
 
     def get_processor(self):